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5 ATSRadar posts tagged #data, covering hiring trends from real ATS data. Latest update Mar 30, 2026.

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How Fast Job Openings Actually Move

ATSRadar analyzed its own historical job and polling data to show how quickly openings appear, change, and disappear, and why applying early matters.

Mar 30, 2026 · 2 min read · ATSRadar

#job market #data #hiring trends #job search #ats

Most job seekers know that "apply early" is good advice. The harder question is: how early actually matters?

Some openings stay active for weeks. Others look fresh one day and are gone the next time you check.

This report uses ATSRadar's own historical jobs and polling data to answer four practical questions:

How long do openings usually remain active after ATSRadar first sees them?
How much of the active market is truly fresh right now?
Do some ATS ecosystems or role families move faster than others?
What should job seekers change if they want to apply earlier?

Key takeaways

Observed median time-to-inactive: 8.95 days for jobs that have already closed after ATSRadar first saw them.
Active jobs are not mostly brand new: the median currently open role has already been in ATSRadar for 24.54 days.
Early closure is real: 14.02% of mature cohorts go inactive within 7 days, and 31.53% are inactive within 14 days, rising to 49.03% within 30 days.
The truly fresh slice is small: only 1.59% of currently active jobs were first seen in the last 24 hours, and 21.30% were first seen in the last 7 days.
What this means for job seekers: the best openings do not vanish instantly across the board, but the early-application edge is strongest in the first 7-14 days.

What "fast-moving" means in this report

This article measures observed opening speed, not the exact amount of time a job has existed on the employer side.

That distinction matters.

First seen means when ATSRadar first ingested the opening.
Inactive means when ATSRadar detected that the opening had left the active set.
postedAt is shown for coverage context only because many ATS records do not provide it consistently enough to anchor lifecycle math.

So when this article says a role "closed within 14 days," it means ATSRadar first saw it, then later detected it inactive within 14 days.

That is the right frame for job seekers deciding how often to check alerts, how quickly to apply, and how much freshness should influence prioritization.

Data breakdown

What the data is measuring

This article measures observed opening speed, not employer-side posted duration. In practice that means we anchor lifecycle math to the moment ATSRadar first sees a job (created_at) and the moment ATSRadar detects it has left the active pool (became_inactive_at).

Current analysis window: 90 days ending 2026-03-31 UTC. Jobs analyzed in-window: 441,014.

Chart 1: Observed time-to-inactive buckets

This chart uses only jobs that have already gone inactive, so it describes observed closed-role lifetimes after ATSRadar first saw the posting.

Share of inactive jobs

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Bucket	Inactive jobs	Share of inactive jobs
<3 days	29,189	16.83%
3-7 days	26,554	15.31%
7-14 days	64,411	37.13%
14-30 days	46,162	26.61%
30+ days	7,156	4.13%

Bucket	Inactive jobs	Share of inactive jobs
<3 days	29,189	16.83%
3-7 days	26,554	15.31%
7-14 days	64,411	37.13%
14-30 days	46,162	26.61%
30+ days	7,156	4.13%

Chart 2: How fresh the current active pool actually is

Share of current active jobs

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First seen bucket	Active jobs	Share of current active jobs
24h	4,263	1.59%
3d	15,411	5.76%
7d	56,978	21.30%
14d	88,103	32.93%

First seen bucket	Active jobs	Share of current active jobs
24h	4,263	1.59%
3d	15,411	5.76%
7d	56,978	21.30%
14d	88,103	32.93%

Chart 3: Daily flow of openings into and out of the active pool

New jobs first seenJobs became inactiveNet active pool change

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Day	New jobs	Jobs became inactive	Net active pool change
2025-12-31	0	0	0
2026-01-01	0	0	0
2026-01-02	0	0	0
2026-01-03	0	0	0
2026-01-04	0	0	0
2026-01-05	0	0	0
2026-01-06	0	0	0
2026-01-07	0	0	0
2026-01-08	0	0	0
2026-01-09	0	0	0
2026-01-10	0	0	0
2026-01-11	0	0	0
2026-01-12	0	0	0
2026-01-13	0	0	0
2026-01-14	0	0	0
2026-01-15	0	0	0
2026-01-16	0	0	0
2026-01-17	0	0	0
2026-01-18	0	0	0
2026-01-19	0	0	0
2026-01-20	0	0	0
2026-01-21	0	0	0
2026-01-22	0	0	0
2026-01-23	0	0	0
2026-01-24	0	0	0
2026-01-25	0	0	0
2026-01-26	0	0	0
2026-01-27	0	0	0
2026-01-28	0	0	0
2026-01-29	0	0	0
2026-01-30	0	0	0
2026-01-31	0	0	0
2026-02-01	0	0	0
2026-02-02	0	0	0
2026-02-03	0	0	0
2026-02-04	0	0	0
2026-02-05	0	0	0
2026-02-06	0	0	0
2026-02-07	0	0	0
2026-02-08	0	0	0
2026-02-09	0	0	0
2026-02-10	0	0	0
2026-02-11	0	0	0
2026-02-12	0	0	0
2026-02-13	0	0	0
2026-02-14	0	0	0
2026-02-15	0	0	0
2026-02-16	0	0	0
2026-02-17	0	0	0
2026-02-18	56,308	366	+55,942
2026-02-19	64,168	777	+63,391
2026-02-20	5,815	3,895	+1,920
2026-02-21	1,091	969	+122
2026-02-22	77	153	-76
2026-02-23	6,522	1,810	+4,712
2026-02-24	5,063	3,737	+1,326
2026-02-25	2,454	2,760	-306
2026-02-26	3,317	3,140	+177
2026-02-27	33,356	29,172	+4,184
2026-02-28	6,167	5,359	+808
2026-03-01	17,612	237	+17,375
2026-03-02	3,487	1,723	+1,764
2026-03-03	3,093	4,449	-1,356
2026-03-04	5,065	4,842	+223
2026-03-05	3,700	3,874	-174
2026-03-06	89,154	3,404	+85,750
2026-03-07	2,880	2,721	+159
2026-03-08	4,891	444	+4,447
2026-03-09	3,525	5,154	-1,629
2026-03-10	3,418	7,794	-4,376
2026-03-11	1,047	973	+74
2026-03-12	2,429	2,150	+279
2026-03-13	3,203	3,081	+122
2026-03-14	703	701	+2
2026-03-15	10,730	10,262	+468
2026-03-16	670	850	-180
2026-03-17	322	265	+57
2026-03-18	3,386	3,394	-8
2026-03-19	17,565	18,878	-1,313
2026-03-20	8,400	6,166	+2,234
2026-03-21	2,890	3,695	-805
2026-03-22	0	2	-2
2026-03-23	1,252	6,952	-5,700
2026-03-24	8,879	5,577	+3,302
2026-03-25	4,126	7	+4,119
2026-03-26	34,904	10,188	+24,716
2026-03-27	748	1,414	-666
2026-03-28	14,126	6,584	+7,542
2026-03-29	210	280	-70
2026-03-30	2,844	5,275	-2,431
2026-03-31	1,420	0	+1,420

Day	New jobs	Jobs became inactive	Net active pool change
2025-12-31	0	0	0
2026-01-01	0	0	0
2026-01-02	0	0	0
2026-01-03	0	0	0
2026-01-04	0	0	0
2026-01-05	0	0	0
2026-01-06	0	0	0

Showing first 7 of 91 rows.

Chart 4: Which ATS ecosystems move faster

Only providers above the minimum volume threshold (5,000 jobs and mature 14-day cohorts) are included.

Share inactive within 14 days

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ATS	Jobs in window	Median observed time-to-inactive	Inactive within 7d	Inactive within 14d	Inactive within 30d
Greenhouse	214,222	13.15 days	6.52%	20.41%	41.18%
Ashby	88,512	8.94 days	15.51%	52.74%	64.10%
Lever	77,072	6.51 days	25.87%	33.33%	41.76%
SmartRecruiters	35,125	5.39 days	27.32%	33.29%	37.50%

ATS	Jobs in window	Median observed time-to-inactive	Inactive within 7d	Inactive within 14d	Inactive within 30d
Greenhouse	214,222	13.15 days	6.52%	20.41%	41.18%
Ashby	88,512	8.94 days	15.51%	52.74%	64.10%
Lever	77,072	6.51 days	25.87%	33.33%	41.76%
SmartRecruiters	35,125	5.39 days	27.32%	33.29%	37.50%

Chart 5: Which role families close faster

Family inference coverage: 66.54% of jobs landed in a non-Other family.

Median observed time-to-inactive (days)

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Role family	Jobs in window	Median observed time-to-inactive	Inactive within 7d	Inactive within 14d	Inactive within 30d
Engineering	85,864	8.94 days	13.61%	33.60%	49.22%
Design	71,990	8.98 days	20.51%	35.43%	48.03%
Security	33,783	12.50 days	10.38%	29.08%	47.91%
Sales	29,214	8.95 days	7.90%	30.72%	50.59%
Operations/RevOps	16,438	8.94 days	11.55%	37.05%	55.75%
Marketing	12,565	8.95 days	11.29%	37.14%	55.78%
Data	9,757	8.95 days	14.53%	33.35%	52.28%
HR/People	9,293	13.10 days	12.61%	40.90%	62.62%
Finance	8,571	9.38 days	9.68%	32.38%	56.34%
Product	6,561	8.98 days	8.92%	31.38%	50.20%

Role family	Jobs in window	Median observed time-to-inactive	Inactive within 7d	Inactive within 14d	Inactive within 30d
Engineering	85,864	8.94 days	13.61%	33.60%	49.22%
Design	71,990	8.98 days	20.51%	35.43%	48.03%
Security	33,783	12.50 days	10.38%	29.08%	47.91%
Sales	29,214	8.95 days	7.90%	30.72%	50.59%
Operations/RevOps	16,438	8.94 days	11.55%	37.05%	55.75%
Marketing	12,565	8.95 days	11.29%	37.14%	55.78%

Showing first 6 of 10 rows.

Geography note

ATSRadar stores a raw country value for only 36.16% of jobs in this historical first-seen window, so this article does not publish country speed rankings. That is deliberate: weak normalization would create false precision.

What job seekers should do with this

If a role matters, treat the first 7-14 days as the highest-value application window instead of assuming it will sit open for a month.
Keep one broad alert for volume and one tighter alert for the exact titles you want, so you can react quickly without drowning in noise.
When a provider or role family in this report moves faster, check those openings daily rather than weekly.
Use freshness as a filter, not a guarantee: a job first seen yesterday is not automatically better, but it is less likely to be late-stage in the hiring process.

Why applying early still matters

The data does not say that every job disappears instantly.

It does say that the first week and the first two weeks matter more than many job seekers assume.

If you only check once a week, you will still catch part of the market. But you will be consistently late on the slice that moves fastest, and that is often the exact slice with the least competition slack.

In practical terms:

Use alerts or searches that surface newly seen roles daily.
Prioritize the first 7-14 days, not just the first 24 hours.
Use freshness to rank your queue, especially in faster ATS ecosystems and faster-moving role families.
Do not rely on postedAt alone when it is missing or stale. First-seen timing is often the more reliable operational signal.

Methodology

Analysis window: 90 days ending 2026-03-31T04:08:06.489Z (UTC).

Dataset coverage: first observed job 2026-02-18T06:53:08.863Z, latest observed lifecycle timestamp 2026-03-31T04:08:06.489Z.

Field choices: first seen = jobs.created_at is used as first seen by ATSRadar because it marks first ingestion into the platform. last seen = jobs.last_seen_at is used as the most recent confirmed observation of an opening. became inactive = jobs.became_inactive_at is used as the detected closure timestamp when a previously active opening drops out of the active set.

postedAt coverage: 219,224 jobs in-window (49.71%).

Role-family coverage: 66.54% classified outside Other.

Exact vs Approximate

Exact: first seen = jobs.created_at (job first ingested by ATSRadar)
Exact: last seen = jobs.last_seen_at (most recent successful observation)
Exact: became inactive = jobs.became_inactive_at (when ATSRadar detected the job left the active set)
Exact: freshness buckets use current active jobs only and first-seen timestamps
Exact: daily flow uses UTC day buckets from created_at and became_inactive_at
Approximate: time-to-inactive is exact to ATSRadar detection time, not the exact moment an employer removed the posting
Approximate: median observed lifetime only covers jobs that have already become inactive inside the analysis window
Approximate: postedAt reflects source-provided employer timestamps and is used for coverage notes only because completeness is mixed
Approximate: older inactive rows that predate became_inactive_at were backfilled from updated_at / last_seen_at / scanned_at fallbacks during migration 0033
Approximate: geography is not published in this article because stored country coverage is not strong enough for a reliable all-cohort speed comparison

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Top Companies Hiring Across the US, Canada, Germany, Spain, the UK, France, and Italy

A 30, 60, and 90-day view of which companies and industries are driving hiring across seven major markets.

Mar 18, 2026 · 2 min read · ATSRadar

#hiring trends #job market #companies #countries #data

Hiring volume by itself is not enough. If you are targeting multiple countries, the better question is: which markets are actually posting now, which employers are driving that volume, and how concentrated is the demand?

This report uses ATSRadar data to compare 30-day, 60-day, and 90-day hiring activity across the United States, Canada, Germany, Spain, the United Kingdom, France, and Italy. The focus is practical: where volume is strongest, where company breadth is wider, and which industries are creating the most opportunity.

Key takeaways

Biggest 90-day market: United States with 133,095 postings and 5,501 distinct hiring companies.
Strongest 30-day volume right now: United States at 83,950 postings in the latest 30-day window.
Fastest recent acceleration: United States (+47,512 postings vs the prior 30 days).
Cooling most vs the previous 30 days: France (+395 postings).
Broadest company base: United States with 5,501 distinct companies across the 90-day view.
Highest concentration: Italy where the top 10 companies account for 68.96% of 90-day postings.

Data coverage

90-day jobs analyzed: 274,959 total postings, with 147,118 (53.51%) inside the seven-country scope.

Coverage quality: country parsed 82.46%, company identity 100.00%, known industry 80.93%, postedAt present 95.82%.

Executive summary

The charts below are built from the same normalized dataset and the same date logic across all seven countries. That makes the 30 / 60 / 90-day comparisons useful for job seekers who want to understand both current volume and recent momentum, instead of relying on a single static ranking.

Cross-country overview

Use the grouped country comparison first to see where total volume sits today, then use the weekly trend and country sections to understand whether that volume is broad-based or concentrated in a smaller group of employers.

Country-by-country breakdown

Each country section includes:

the top hiring companies
the industries driving the most postings
30 / 60 / 90-day exact-value tables
a short read on whether the latest 30-day window is accelerating or cooling

Executive summary

This snapshot compares seven markets using the same ATSRadar dataset and the same date logic across 30, 60, and 90 days. The goal is not raw board-size parity with LinkedIn or Glassdoor, but a cleaner read on where hiring is concentrated, which employers are posting the most roles, and which industries are driving that demand.

Cross-country overview

By 90-day volume, the strongest markets in this snapshot are United States, United Kingdom, and Canada. Recent momentum is strongest in United States, Canada, and United Kingdom.

Chart 1: Total postings by country (30 / 60 / 90 days)

Last 30 daysLast 60 daysLast 90 days

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Country	30-day postings	60-day postings	90-day postings	Distinct companies (90d)	Recent 30 vs prior 30	Top 10 concentration (90d)
United States	83950	120388	133095	5501	+47,512	13.75%
United Kingdom	3233	5484	5744	656	+982	29.70%
Canada	1984	2730	2897	434	+1,238	20.12%
Germany	1458	2101	2208	277	+815	40.94%
Spain	895	1255	1295	166	+535	44.71%
France	773	1151	1254	169	+395	43.54%
Italy	489	580	625	80	+398	68.96%

Country	30-day postings	60-day postings	90-day postings	Distinct companies (90d)	Recent 30 vs prior 30	Top 10 concentration (90d)
United States	83950	120388	133095	5501	+47,512	13.75%
United Kingdom	3233	5484	5744	656	+982	29.70%
Canada	1984	2730	2897	434	+1,238	20.12%
Germany	1458	2101	2208	277	+815	40.94%
Spain	895	1255	1295	166	+535	44.71%
France	773	1151	1254	169	+395	43.54%
Italy	489	580	625	80	+398	68.96%

Chart 2: Weekly posting volume by country (last 90 days)

United StatesCanadaGermanySpainUnited KingdomFranceItaly

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Week start (UTC)	United States	Canada	Germany	Spain	United Kingdom	France	Italy
2025-12-15	326	3	4	0	18	0	0
2025-12-22	1111	11	13	3	12	12	2
2025-12-29	1585	20	7	5	23	17	5
2026-01-05	4087	63	40	22	79	34	21
2026-01-12	5616	70	44	10	128	40	17
2026-01-19	5281	129	71	24	167	49	15
2026-01-26	7228	145	179	64	205	63	9
2026-02-02	9634	224	137	32	246	115	10
2026-02-09	12401	216	220	128	1556	114	43
2026-02-16	14874	313	262	232	539	190	52
2026-02-23	18970	491	328	201	871	194	48
2026-03-02	24083	555	373	297	941	178	352
2026-03-09	18551	459	268	182	720	158	27
2026-03-16	9348	198	262	95	239	90	24

Week start (UTC)	United States	Canada	Germany	Spain	United Kingdom	France	Italy
2025-12-15	326	3	4	0	18	0	0
2025-12-22	1111	11	13	3	12	12	2
2025-12-29	1585	20	7	5	23	17	5
2026-01-05	4087	63	40	22	79	34	21
2026-01-12	5616	70	44	10	128	40	17

Showing first 5 of 14 rows.

Chart 3: How concentrated hiring is by country

Higher values mean a smaller set of employers is driving more of the observed volume.

Top 10 company share (90d)

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Country	Top 10 company share (90d)	Distinct companies (90d)
United States	13.75%	5501
United Kingdom	29.70%	656
Canada	20.12%	434
Germany	40.94%	277
Spain	44.71%	166
France	43.54%	169
Italy	68.96%	80

Country	Top 10 company share (90d)	Distinct companies (90d)
United States	13.75%	5501
United Kingdom	29.70%	656
Canada	20.12%	434
Germany	40.94%	277
Spain	44.71%	166
France	43.54%	169
Italy	68.96%	80

Country-by-country breakdown

United States

United States logged 83,950 postings in the last 30 days, 120,388 in 60 days, and 133,095 in 90 days. The latest 30-day window is accelerating (+47,512 vs the prior 30 days), and the market spans 5,501 distinct companies over 90 days.

Top-10 company concentration: 30d 17.19%, 60d 14.74%, 90d 13.75%.

Top hiring companies in United States (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Carvana	1976	2.35%	2689	2.23%	2934	2.20%
Centriaautism	2286	2.72%	2660	2.21%	2714	2.04%
Lifestance	1256	1.50%	2271	1.89%	2485	1.87%
Andurilindustries	2027	2.41%	2028	1.68%	2028	1.52%
Equipmentsharecom	1708	2.03%	1708	1.42%	1708	1.28%
Spacex	344	0.41%	1558	1.29%	1558	1.17%
Speechify	1525	1.82%	1540	1.28%	1540	1.16%
Cgsfederal	1173	1.40%	1246	1.03%	1261	0.95%
Renuity	841	1.00%	1202	1.00%	1232	0.93%
Veterinaryemergencygroupst	840	1.00%	840	0.70%	840	0.63%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Carvana	1976	2.35%	2689	2.23%	2934	2.20%
Centriaautism	2286	2.72%	2660	2.21%	2714	2.04%
Lifestance	1256	1.50%	2271	1.89%	2485	1.87%
Andurilindustries	2027	2.41%	2028	1.68%	2028	1.52%
Equipmentsharecom	1708	2.03%	1708	1.42%	1708	1.28%

Showing first 5 of 10 rows.

Top industries in United States (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	21307	25.38%	31152	25.88%	34951	26.26%
Other/Unknown	12754	15.19%	18039	14.98%	20111	15.11%
AI/ML	10245	12.20%	16763	13.92%	19098	14.35%
Marketplace/Logistics	13597	16.20%	17062	14.17%	18050	13.56%
Healthcare	10577	12.60%	15174	12.60%	16381	12.31%
Cybersecurity	4682	5.58%	7542	6.26%	8560	6.43%
Fintech	4301	5.12%	5474	4.55%	5825	4.38%
Education	2314	2.76%	3413	2.84%	3772	2.83%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	21307	25.38%	31152	25.88%	34951	26.26%
Other/Unknown	12754	15.19%	18039	14.98%	20111	15.11%
AI/ML	10245	12.20%	16763	13.92%	19098	14.35%
Marketplace/Logistics	13597	16.20%	17062	14.17%	18050	13.56%
Healthcare	10577	12.60%	15174	12.60%	16381	12.31%

Showing first 5 of 8 rows.

Canada

Canada logged 1,984 postings in the last 30 days, 2,730 in 60 days, and 2,897 in 90 days. The latest 30-day window is accelerating (+1,238 vs the prior 30 days), and the market spans 434 distinct companies over 90 days.

Top-10 company concentration: 30d 26.61%, 60d 21.17%, 90d 20.12%.

Top hiring companies in Canada (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Clutch	91	4.59%	119	4.36%	122	4.21%
Lightspeedhq	84	4.23%	85	3.11%	85	2.93%
2k	50	2.52%	54	1.98%	54	1.86%
Monks	52	2.62%	52	1.90%	52	1.79%
Appdirect	40	2.02%	49	1.79%	49	1.69%
Industrialelectricmanufacturing	48	2.42%	48	1.76%	48	1.66%
Mthreerecruitingportal	48	2.42%	48	1.76%	48	1.66%
Lightspeedhqfr	41	2.07%	42	1.54%	42	1.45%
Airbnb	28	1.41%	40	1.47%	42	1.45%
Sonypicturesimageworks	9	0.45%	41	1.50%	41	1.42%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Clutch	91	4.59%	119	4.36%	122	4.21%
Lightspeedhq	84	4.23%	85	3.11%	85	2.93%
2k	50	2.52%	54	1.98%	54	1.86%
Monks	52	2.62%	52	1.90%	52	1.79%
Appdirect	40	2.02%	49	1.79%	49	1.69%

Showing first 5 of 10 rows.

Top industries in Canada (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	907	45.72%	1233	45.16%	1322	45.63%
Other/Unknown	297	14.97%	410	15.02%	416	14.36%
AI/ML	192	9.68%	305	11.17%	327	11.29%
Marketplace/Logistics	150	7.56%	195	7.14%	202	6.97%
Fintech	134	6.75%	176	6.45%	183	6.32%
Cybersecurity	87	4.39%	119	4.36%	138	4.76%
Healthcare	66	3.33%	118	4.32%	121	4.18%
E-commerce/Consumer	80	4.03%	94	3.44%	107	3.69%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	907	45.72%	1233	45.16%	1322	45.63%
Other/Unknown	297	14.97%	410	15.02%	416	14.36%
AI/ML	192	9.68%	305	11.17%	327	11.29%
Marketplace/Logistics	150	7.56%	195	7.14%	202	6.97%
Fintech	134	6.75%	176	6.45%	183	6.32%

Showing first 5 of 8 rows.

Germany

Germany logged 1,458 postings in the last 30 days, 2,101 in 60 days, and 2,208 in 90 days. The latest 30-day window is accelerating (+815 vs the prior 30 days), and the market spans 277 distinct companies over 90 days.

Top-10 company concentration: 30d 52.13%, 60d 42.22%, 90d 40.94%.

Top hiring companies in Germany (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Teampicnic	209	14.33%	254	12.09%	254	11.50%
Wppmedia	138	9.47%	138	6.57%	138	6.25%
Doctolib	76	5.21%	76	3.62%	76	3.44%
Wolt	37	2.54%	72	3.43%	72	3.26%
Isaraerospace	67	4.60%	69	3.28%	69	3.13%
The Exploration Company	29	1.99%	53	2.52%	69	3.13%
Boltv2	58	3.98%	60	2.86%	60	2.72%
Celonis	55	3.77%	57	2.71%	58	2.63%
Black Semiconductor GmbH	10	0.69%	55	2.62%	55	2.49%
Databricks	53	3.64%	53	2.52%	53	2.40%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Teampicnic	209	14.33%	254	12.09%	254	11.50%
Wppmedia	138	9.47%	138	6.57%	138	6.25%
Doctolib	76	5.21%	76	3.62%	76	3.44%
Wolt	37	2.54%	72	3.43%	72	3.26%
Isaraerospace	67	4.60%	69	3.28%	69	3.13%

Showing first 5 of 10 rows.

Top industries in Germany (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	519	35.60%	691	32.89%	727	32.93%
Marketplace/Logistics	361	24.76%	458	21.80%	467	21.15%
AI/ML	164	11.25%	304	14.47%	338	15.31%
Other/Unknown	129	8.85%	220	10.47%	229	10.37%
Cybersecurity	98	6.72%	133	6.33%	141	6.39%
Media/Entertainment	61	4.18%	79	3.76%	79	3.58%
Fintech	40	2.74%	59	2.81%	61	2.76%
Healthcare	24	1.65%	53	2.52%	55	2.49%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	519	35.60%	691	32.89%	727	32.93%
Marketplace/Logistics	361	24.76%	458	21.80%	467	21.15%
AI/ML	164	11.25%	304	14.47%	338	15.31%
Other/Unknown	129	8.85%	220	10.47%	229	10.37%
Cybersecurity	98	6.72%	133	6.33%	141	6.39%

Showing first 5 of 8 rows.

Spain

Spain logged 895 postings in the last 30 days, 1,255 in 60 days, and 1,295 in 90 days. The latest 30-day window is accelerating (+535 vs the prior 30 days), and the market spans 166 distinct companies over 90 days.

Top-10 company concentration: 30d 48.94%, 60d 45.66%, 90d 44.71%.

Top hiring companies in Spain (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Brainrocketltd	44	4.92%	120	9.56%	120	9.27%
Celonis	75	8.38%	81	6.45%	81	6.25%
Superbet	70	7.82%	70	5.58%	70	5.41%
Scopely	63	7.04%	63	5.02%	63	4.86%
Neoris	43	4.80%	53	4.22%	55	4.25%
Alan	19	2.12%	46	3.67%	46	3.55%
Bitpanda	41	4.58%	43	3.43%	43	3.32%
Appodeal	11	1.23%	37	2.95%	37	2.86%
Diamondfoundry	15	1.68%	17	1.35%	33	2.55%
Speechify	29	3.24%	31	2.47%	31	2.39%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Brainrocketltd	44	4.92%	120	9.56%	120	9.27%
Celonis	75	8.38%	81	6.45%	81	6.25%
Superbet	70	7.82%	70	5.58%	70	5.41%
Scopely	63	7.04%	63	5.02%	63	4.86%
Neoris	43	4.80%	53	4.22%	55	4.25%

Showing first 5 of 10 rows.

Top industries in Spain (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	481	53.74%	673	53.63%	696	53.75%
AI/ML	97	10.84%	156	12.43%	163	12.59%
Other/Unknown	107	11.96%	141	11.24%	142	10.97%
Fintech	67	7.49%	79	6.29%	81	6.25%
Cybersecurity	35	3.91%	61	4.86%	62	4.79%
Marketplace/Logistics	37	4.13%	49	3.90%	49	3.78%
Healthcare	27	3.02%	31	2.47%	31	2.39%
E-commerce/Consumer	18	2.01%	28	2.23%	31	2.39%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	481	53.74%	673	53.63%	696	53.75%
AI/ML	97	10.84%	156	12.43%	163	12.59%
Other/Unknown	107	11.96%	141	11.24%	142	10.97%
Fintech	67	7.49%	79	6.29%	81	6.25%
Cybersecurity	35	3.91%	61	4.86%	62	4.79%

Showing first 5 of 8 rows.

United Kingdom

United Kingdom logged 3,233 postings in the last 30 days, 5,484 in 60 days, and 5,744 in 90 days. The latest 30-day window is accelerating (+982 vs the prior 30 days), and the market spans 656 distinct companies over 90 days.

Top-10 company concentration: 30d 23.91%, 60d 31.09%, 90d 29.70%.

Top hiring companies in United Kingdom (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Privateequityinsights	0	0.00%	570	10.39%	570	9.92%
Unitedmedia	0	0.00%	181	3.30%	181	3.15%
Cfoinsights	0	0.00%	177	3.23%	177	3.08%
Hrtechx	0	0.00%	173	3.15%	173	3.01%
Wppmedia	159	4.92%	159	2.90%	159	2.77%
Sohohouseco	92	2.85%	123	2.24%	123	2.14%
Bjak	110	3.40%	114	2.08%	115	2.00%
Anaplan	59	1.82%	71	1.29%	71	1.24%
Graphcore	70	2.17%	70	1.28%	70	1.22%
Janestreet	65	2.01%	67	1.22%	67	1.17%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Privateequityinsights	0	0.00%	570	10.39%	570	9.92%
Unitedmedia	0	0.00%	181	3.30%	181	3.15%
Cfoinsights	0	0.00%	177	3.23%	177	3.08%
Hrtechx	0	0.00%	173	3.15%	173	3.01%
Wppmedia	159	4.92%	159	2.90%	159	2.77%

Showing first 5 of 10 rows.

Top industries in United Kingdom (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	1154	35.69%	1620	29.54%	1738	30.26%
AI/ML	515	15.93%	1100	20.06%	1147	19.97%
Other/Unknown	470	14.54%	907	16.54%	934	16.26%
Marketplace/Logistics	246	7.61%	657	11.98%	675	11.75%
Cybersecurity	261	8.07%	361	6.58%	387	6.74%
Fintech	137	4.24%	231	4.21%	242	4.21%
E-commerce/Consumer	159	4.92%	198	3.61%	202	3.52%
Healthcare	142	4.39%	187	3.41%	193	3.36%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	1154	35.69%	1620	29.54%	1738	30.26%
AI/ML	515	15.93%	1100	20.06%	1147	19.97%
Other/Unknown	470	14.54%	907	16.54%	934	16.26%
Marketplace/Logistics	246	7.61%	657	11.98%	675	11.75%
Cybersecurity	261	8.07%	361	6.58%	387	6.74%

Showing first 5 of 8 rows.

France

France logged 773 postings in the last 30 days, 1,151 in 60 days, and 1,254 in 90 days. The latest 30-day window is accelerating (+395 vs the prior 30 days), and the market spans 169 distinct companies over 90 days.

Top-10 company concentration: 30d 53.43%, 60d 44.48%, 90d 43.54%.

Top hiring companies in France (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Doctolib	135	17.46%	137	11.90%	137	10.93%
Alan	48	6.21%	68	5.91%	87	6.94%
Wppmedia	51	6.60%	51	4.43%	51	4.07%
Artefactlinkedin	23	2.98%	45	3.91%	45	3.59%
Artefact	23	2.98%	40	3.48%	40	3.19%
Teampicnic	31	4.01%	39	3.39%	39	3.11%
Artefactjobs	21	2.72%	39	3.39%	39	3.11%
The Exploration Company	15	1.94%	32	2.78%	38	3.03%
Ledger	4	0.52%	28	2.43%	37	2.95%
Alma31	21	2.72%	30	2.61%	33	2.63%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Doctolib	135	17.46%	137	11.90%	137	10.93%
Alan	48	6.21%	68	5.91%	87	6.94%
Wppmedia	51	6.60%	51	4.43%	51	4.07%
Artefactlinkedin	23	2.98%	45	3.91%	45	3.59%
Artefact	23	2.98%	40	3.48%	40	3.19%

Showing first 5 of 10 rows.

Top industries in France (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	358	46.31%	498	43.27%	533	42.50%
AI/ML	122	15.78%	206	17.90%	231	18.42%
Other/Unknown	94	12.16%	126	10.95%	142	11.32%
Marketplace/Logistics	93	12.03%	120	10.43%	124	9.89%
Cybersecurity	53	6.86%	95	8.25%	107	8.53%
E-commerce/Consumer	13	1.68%	28	2.43%	28	2.23%
Media/Entertainment	18	2.33%	22	1.91%	24	1.91%
Healthcare	7	0.91%	21	1.82%	21	1.67%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Software/SaaS	358	46.31%	498	43.27%	533	42.50%
AI/ML	122	15.78%	206	17.90%	231	18.42%
Other/Unknown	94	12.16%	126	10.95%	142	11.32%
Marketplace/Logistics	93	12.03%	120	10.43%	124	9.89%
Cybersecurity	53	6.86%	95	8.25%	107	8.53%

Showing first 5 of 8 rows.

Italy

Italy logged 489 postings in the last 30 days, 580 in 60 days, and 625 in 90 days. The latest 30-day window is accelerating (+398 vs the prior 30 days), and the market spans 80 distinct companies over 90 days.

Top-10 company concentration: 30d 74.85%, 60d 70.17%, 90d 68.96%.

Top hiring companies in Italy (last 90 days)

90-day postings

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Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Jdsports	280	57.26%	280	48.28%	280	44.80%
Satispay	8	1.64%	27	4.66%	44	7.04%
Deel	8	1.64%	23	3.97%	27	4.32%
Wppmedia	15	3.07%	15	2.59%	15	2.40%
The Exploration Company	6	1.23%	7	1.21%	13	2.08%
Speechify	9	1.84%	12	2.07%	12	1.92%
Cfoinsights	10	2.04%	10	1.72%	10	1.60%
Jensenhughes	10	2.04%	10	1.72%	10	1.60%
Privateequityinsights	10	2.04%	10	1.72%	10	1.60%
Unitedmedia	10	2.04%	10	1.72%	10	1.60%

Company	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
Jdsports	280	57.26%	280	48.28%	280	44.80%
Satispay	8	1.64%	27	4.66%	44	7.04%
Deel	8	1.64%	23	3.97%	27	4.32%
Wppmedia	15	3.07%	15	2.59%	15	2.40%
The Exploration Company	6	1.23%	7	1.21%	13	2.08%

Showing first 5 of 10 rows.

Top industries in Italy (last 90 days)

90-day postings

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Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
E-commerce/Consumer	281	57.46%	289	49.83%	289	46.24%
Software/SaaS	67	13.70%	102	17.59%	122	19.52%
AI/ML	22	4.50%	41	7.07%	54	8.64%
Cybersecurity	23	4.70%	43	7.41%	49	7.84%
Marketplace/Logistics	31	6.34%	33	5.69%	33	5.28%
Other/Unknown	29	5.93%	30	5.17%	33	5.28%
Media/Entertainment	18	3.68%	18	3.10%	18	2.88%
Fintech	8	1.64%	9	1.55%	11	1.76%

Industry	30-day postings	30-day share	60-day postings	60-day share	90-day postings	90-day share
E-commerce/Consumer	281	57.46%	289	49.83%	289	46.24%
Software/SaaS	67	13.70%	102	17.59%	122	19.52%
AI/ML	22	4.50%	41	7.07%	54	8.64%
Cybersecurity	23	4.70%	43	7.41%	49	7.84%
Marketplace/Logistics	31	6.34%	33	5.69%	33	5.28%

Showing first 5 of 8 rows.

What job seekers should do with this

If you are open to relocation or international scope, start with United States, United Kingdom, and Canada for sheer volume and layer in United States, Canada, and United Kingdom for momentum. For industry targeting, the strongest recurring buckets across these seven markets are Software/SaaS, AI/ML, Marketplace/Logistics, Healthcare, and Cybersecurity.

Use one alert per target country so you can tune titles, exclusions, and cadence to each market instead of merging everything into one feed.
Prioritize countries where both 30-day volume and 90-day company breadth are strong; that usually means more room to pivot if one employer slows down.
If a country is highly concentrated, shortlist the top employers directly and monitor them closely because a small number of companies are driving most of the opportunity.
If you are flexible on industry, start with Software/SaaS, AI/ML, Marketplace/Logistics before widening into lower-volume niches.

Methodology and limitations

Methodology

Windows: rolling 30, 60, and 90 days ending 2026-03-19 (UTC).

Date field: Job date uses postedAt when available; scannedAt is used only when postedAt is missing.

Company grouping: Company grouping uses normalized jobs.company text (lowercased, punctuation stripped, whitespace collapsed).

Industry mapping: Industry uses company metadata first, then category/department hints, then deterministic keyword inference. This post rolls industries into a stable cross-country taxonomy.

Country normalization: Country uses normalized location parsing with aliases such as US/USA/United States -> United States and UK/Great Britain/United Kingdom -> United Kingdom.

Active-job policy: Rankings use unique postings observed inside each rolling window rather than filtering to current isActive=true, because current active state can undercount historical hiring activity inside 60/90-day windows.

Coverage: country parsed 82.46%, company identity 100.00%, known industry 80.93%, postedAt present 95.82%, scannedAt fallback 4.18%.

Limitations

The article is scoped to United States, Canada, Germany, Spain, United Kingdom, France, and Italy only, so it is not a full view of all ATSRadar coverage.
Country parsing depends on ATS free-text location fields; some rows stay unknown/unparsed and are excluded from these rankings.
Company identity is grouped from normalized company-name text, so rare edge-case spelling variants can still split one employer into multiple groups.
Industry can come from company metadata, structured hints, or deterministic inference; anything ambiguous rolls into Other/Unknown and is kept out of top-industry rankings when possible.
The current active flag is reported for transparency (68.42% of 90-day rows are still active), but the ranking itself measures posting activity observed inside each window rather than only jobs still open today.

Track this automatically with ATSRadar

If you want this broken down for your own titles, exclusions, countries, and update cadence, create alerts directly inside ATSRadar instead of checking country rankings manually each week.

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Entry-Level vs Senior: Where the Market Actually Is (Last 90 Days)

A data-driven look at hiring levels by industry and geography—so you can target your job search.

Mar 6, 2026 · 1 min read · ATSRadar

#job market #seniority #hiring trends #data

Hiring volume alone does not tell you where to spend time. The better question is: what level mix is each market hiring for right now?

This report uses the latest ATSRadar snapshot to compare IC vs Manager vs Director vs VP/Head across industries and geographies.

Key takeaways

Across 521,819 postings in the last 90 days, the market mix is 76.61% IC, 17.84% Manager, 3.43% Director, and 2.12% VP/Head.
Senior leadership share (Director + VP/Head + C-level) is 5.55% (-0.06 pp vs the latest 30-day window).
For junior/IC searches right now, the strongest industry mix is in Education, AI/ML, and Marketplace/Logistics.
For manager+ searches, the highest Director/VP concentration is in Fintech, Government/Nonprofit, and Healthcare.
Geographically, senior-heavy demand clusters in United Kingdom, Singapore, and United States, while IC-heavy U.S. states include Michigan, Ohio, and Maryland.

How level is defined in this report

We normalize each role into a level bucket using deterministic rules on title + seniority text (and trimmed description for context):

C-level
VP / Head
Director
Manager
Junior IC
IC (default)

If a title contains multiple labels (for example, Director/Manager), the higher bucket wins.

Data breakdown

What we measured

Window: last 90 days in UTC. Date uses postedAt, with scannedAt fallback when missing.

Level buckets use a deterministic rule order: C-level > VP/Head > Director > Manager > Junior IC > IC default.

Chart A: Overall seniority distribution

ICManagerDirectorVP/Head

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The 30-day bar is included for context so you can spot recent mix shifts.

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Level	Jobs (last 90d)	Share
Junior IC	26,256	5.03%
IC	373,510	71.58%
Manager	93,082	17.84%
Director	17,924	3.43%
VP / Head	8,373	1.60%
C-level	2,674	0.51%

Level	Jobs (last 90d)	Share
Junior IC	26,256	5.03%
IC	373,510	71.58%
Manager	93,082	17.84%
Director	17,924	3.43%
VP / Head	8,373	1.60%

Showing first 5 of 6 rows.

Chart B: Weekly trend of level mix

ICManagerDirectorVP/Head

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Weekly points reduce day-to-day noise and make mix changes easier to read.

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Week start (UTC)	Total jobs	IC	Manager	Director	VP/Head
2026-02-09	10,219	68.72%	23.83%	4.34%	3.11%
2026-02-16	16,642	70.85%	22.83%	3.52%	2.80%
2026-02-23	22,359	74.73%	19.71%	3.29%	2.27%
2026-03-02	24,942	77.12%	17.79%	2.96%	2.13%
2026-03-09	18,431	78.49%	16.97%	2.66%	1.88%
2026-03-16	18,230	77.43%	17.44%	2.87%	2.26%
2026-03-23	31,780	73.68%	20.48%	3.51%	2.33%
2026-03-30	39,679	77.48%	17.42%	2.94%	2.16%
2026-04-06	26,150	75.35%	18.80%	3.67%	2.17%
2026-04-13	50,249	81.33%	14.86%	2.08%	1.73%
2026-04-20	28,477	74.72%	19.48%	3.68%	2.12%
2026-04-27	58,793	78.53%	16.29%	3.43%	1.76%
2026-05-04	161,481	77.18%	16.88%	3.83%	2.12%
2026-05-11	14,387	66.89%	24.45%	6.08%	2.59%

Week start (UTC)	Total jobs	IC	Manager	Director	VP/Head
2026-02-09	10,219	68.72%	23.83%	4.34%	3.11%
2026-02-16	16,642	70.85%	22.83%	3.52%	2.80%
2026-02-23	22,359	74.73%	19.71%	3.29%	2.27%
2026-03-02	24,942	77.12%	17.79%	2.96%	2.13%
2026-03-09	18,431	78.49%	16.97%	2.66%	1.88%

Showing first 5 of 14 rows.

Chart C: Industries with highest junior/IC share

Junior/IC share

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Only industries above 200 jobs are included to reduce noise.

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Industry	Total jobs	Junior/IC share	Manager	Director	VP/Head
Education	11,699	87.54%	8.57%	2.75%	1.14%
AI/ML	72,918	82.24%	13.20%	2.21%	2.35%
Marketplace/Logistics	119,915	80.13%	14.93%	2.80%	2.14%
Healthcare	45,390	76.23%	17.40%	5.34%	1.04%
Cybersecurity	25,736	75.18%	18.60%	4.33%	1.89%
Energy/Climate	3,469	74.43%	19.95%	3.52%	2.10%
Government/Nonprofit	6,726	73.27%	19.22%	5.38%	2.13%
Fintech	33,858	70.15%	22.21%	4.91%	2.72%
Software/SaaS	128,525	70.08%	23.56%	4.03%	2.33%
E-commerce/Consumer	10,829	70.08%	25.24%	2.36%	2.32%

Industry	Total jobs	Junior/IC share	Manager	Director	VP/Head
Education	11,699	87.54%	8.57%	2.75%	1.14%
AI/ML	72,918	82.24%	13.20%	2.21%	2.35%
Marketplace/Logistics	119,915	80.13%	14.93%	2.80%	2.14%
Healthcare	45,390	76.23%	17.40%	5.34%	1.04%
Cybersecurity	25,736	75.18%	18.60%	4.33%	1.89%

Showing first 5 of 10 rows.

Chart D: Industries with highest Director/VP share

Director+VP share

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This highlights where management and leadership roles are a larger part of hiring mix.

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Industry	Total jobs	Director+VP share	IC	Manager	Director	VP/Head
Fintech	33,858	7.63%	70.15%	22.21%	4.91%	2.72%
Government/Nonprofit	6,726	7.51%	73.27%	19.22%	5.38%	2.13%
Healthcare	45,390	6.37%	76.23%	17.40%	5.34%	1.04%
Software/SaaS	128,525	6.36%	70.08%	23.56%	4.03%	2.33%
Cybersecurity	25,736	6.22%	75.18%	18.60%	4.33%	1.89%
Energy/Climate	3,469	5.62%	74.43%	19.95%	3.52%	2.10%
Marketplace/Logistics	119,915	4.94%	80.13%	14.93%	2.80%	2.14%
E-commerce/Consumer	10,829	4.68%	70.08%	25.24%	2.36%	2.32%
AI/ML	72,918	4.55%	82.24%	13.20%	2.21%	2.35%
Education	11,699	3.89%	87.54%	8.57%	2.75%	1.14%

Industry	Total jobs	Director+VP share	IC	Manager	Director	VP/Head
Fintech	33,858	7.63%	70.15%	22.21%	4.91%	2.72%
Government/Nonprofit	6,726	7.51%	73.27%	19.22%	5.38%	2.13%
Healthcare	45,390	6.37%	76.23%	17.40%	5.34%	1.04%
Software/SaaS	128,525	6.36%	70.08%	23.56%	4.03%	2.33%
Cybersecurity	25,736	6.22%	75.18%	18.60%	4.33%	1.89%

Showing first 5 of 10 rows.

Chart E: Countries ranked by Director/VP share

Director+VP share

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Unknown country rows are excluded from rankings and tracked in data coverage below.

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Country	Total jobs	Director+VP share	IC	Manager	Director	VP/Head
United Kingdom	10,509	11.62%	63.13%	25.25%	6.15%	5.47%
Singapore	2,683	10.40%	64.63%	24.97%	6.90%	3.50%
United States	253,029	6.67%	73.41%	19.92%	4.33%	2.34%
Germany	3,901	5.97%	67.26%	26.76%	3.59%	2.38%
Canada	6,507	5.90%	74.50%	19.59%	3.95%	1.95%
Spain	2,566	4.83%	70.46%	24.71%	2.92%	1.91%
Netherlands	2,208	4.57%	72.92%	22.51%	2.45%	2.13%
India	7,663	3.69%	73.61%	22.69%	3.07%	0.63%
Ireland	1,779	2.87%	72.01%	25.13%	1.97%	0.90%
France	4,359	2.78%	84.72%	12.50%	1.49%	1.28%

Country	Total jobs	Director+VP share	IC	Manager	Director	VP/Head
United Kingdom	10,509	11.62%	63.13%	25.25%	6.15%	5.47%
Singapore	2,683	10.40%	64.63%	24.97%	6.90%	3.50%
United States	253,029	6.67%	73.41%	19.92%	4.33%	2.34%
Germany	3,901	5.97%	67.26%	26.76%	3.59%	2.38%
Canada	6,507	5.90%	74.50%	19.59%	3.95%	1.95%

Showing first 5 of 10 rows.

Chart F: U.S. states ranked by IC share

IC share

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State ranking uses U.S.-parsed rows only and applies the same minimum-volume threshold.

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State	Total jobs	IC share	Manager	Director	VP/Head
Michigan	4,675	89.65%	8.47%	1.13%	0.75%
Ohio	5,216	83.99%	13.08%	2.30%	0.63%
Maryland	5,047	83.83%	13.30%	1.82%	1.05%
Virginia	7,269	81.81%	14.86%	2.02%	1.31%
Arizona	4,486	81.68%	14.87%	2.43%	1.03%
Pennsylvania	5,509	81.63%	14.58%	2.50%	1.29%
Texas	15,109	80.66%	15.63%	2.40%	1.31%
Georgia	4,355	80.00%	15.71%	2.87%	1.42%
North Carolina	4,874	79.42%	15.63%	3.30%	1.64%
Florida	8,210	78.39%	18.03%	2.12%	1.46%

State	Total jobs	IC share	Manager	Director	VP/Head
Michigan	4,675	89.65%	8.47%	1.13%	0.75%
Ohio	5,216	83.99%	13.08%	2.30%	0.63%
Maryland	5,047	83.83%	13.30%	1.82%	1.05%
Virginia	7,269	81.81%	14.86%	2.02%	1.31%
Arizona	4,486	81.68%	14.87%	2.43%	1.03%

Showing first 5 of 10 rows.

If you're entry-level / junior / IC

Focus first on Education, AI/ML, Marketplace/Logistics, and Healthcare and geo targets like Michigan, Ohio, United States, and United Kingdom.

Alert titles: software engineer, data analyst, product analyst, associate, junior.
Include keywords: entry level, new grad, associate, 0-2 years.
Exclude noise: principal, director, vp, head of.
Use one broad country alert plus one narrow state/city alert to balance volume and precision.

If you're manager+

Prioritize Fintech, Government/Nonprofit, Healthcare, and Software/SaaS and geos like United Kingdom, Singapore, United States, and Germany.

Alert titles: engineering manager, director, head of, vp.
Include keywords: people leadership, org design, cross-functional leadership.
Exclude noise: intern, junior, associate, individual contributor only.
Set location filters to top countries/states from this snapshot and refresh those filters weekly.

Methodology and limitations

Methodology

Window: 90 days ending 2026-05-11T08:12:47.822Z (UTC).

Date coverage: postedAt present 27.75%; scannedAt fallback 72.25%.

Level inference: Level buckets are deterministic and ordered: C-level > VP/Head > Director > Manager > Junior IC > IC default. Matching uses normalized title, seniority text, and trimmed description.

Industry inference: Industry uses company metadata first, then category/department mapping, then deterministic keyword inference from company/title/description.

Geography extraction: Country and U.S. state are parsed from normalized location text. Unknown geography is excluded from Top N rankings and reported in data coverage.

Thresholds: industry charts use at least 200 jobs; geo charts use at least 100 jobs.

Limitations

Titles can include mixed labels (for example, Director/Manager), so rule-based bucketing is directional.
Location parsing depends on ATS free-text fields; some rows remain unknown/unparsed.
Industry can be inferred when structured metadata is missing.
This is a rolling snapshot, so rankings can move week to week.

Coverage: parsed country 81.27%, parsed U.S. state 75.09%, known industry 87.97%, explicit level signal 28.42%.

Track this automatically in your own alerts

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Where the Hiring Is: Top Cities & Regions by Net-New Roles (Last 30 Days)

Hiring hotspots vs cooling markets—ranked by net-new postings and normalized by company presence.

Mar 3, 2026 · 1 min read · ATSRadar

#hiring trends #job market #geography #data

What to do this month (remote/hybrid/relocation)

If you're open to relocation or hybrid, prioritize San Carlos, California (United States), Manila, Manila (Philippines (hybrid)), Bangalore, Bangalore (India), Noida, Uttar Pradesh (India), and Hybrid - San Francisco, California (United States) first.

For remote searches, set country-specific alerts for United States, United Kingdom, and Canada.

When applying in the hottest metros, submit within 24-48 hours because net-new volume is moving quickly.

Keep one alert for your primary target metro and one backup alert for a rising adjacent market.

Re-check this ranking weekly and move effort away from cooling markets.

Key takeaways

Total net-new postings (last 30 days): 318,256 vs 118,324 in the prior window (+199,932).
Top country by net-new postings: United States (+876 vs prior 30 days).
Top normalized metro: San Carlos, California (United States) at 590,000.0 postings per 10k active companies.
Top metro by absolute postings: Chicago, Illinois (United States) (62 postings).
Biggest riser: San Carlos, California (United States) (+56 vs prior 30 days).
Largest cooling market: London, London (hybrid) (-14 vs prior 30 days).

Data coverage

Parsed country coverage: 82.84% (263,634 of 318,256 postings).

Parsed city coverage: 74.47% (237,009 of 318,256 postings).

Unknown/unparsed values are excluded from Top N rankings and tracked separately here.

Hiring demand is not moving evenly across markets. Some metros are accelerating on both volume and density, while others are cooling after a stronger prior month.

Where the hiring is shifting

What we measured

Net-new postings: postings in the last 30 days minus postings in the prior 30-day window.

Job density (normalized rate): postings_last30 / active_companies_180d * 10,000. This controls for company presence in each metro rather than total population size.

Chart A: Top countries by net-new postings

Net-new postings

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Country	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
United States	1513	637	+876	+137.5%
CA (hybrid)	184	39	+145	+371.8%
India	122	31	+91	+293.6%
New York (hybrid)	52	4	+48	+1200.0%
Philippines	48	2	+46	+2300.0%
Philippines (hybrid)	37	5	+32	+640.0%
Canada	38	11	+27	+245.4%
IL (hybrid Workplace)	29	5	+24	+480.0%
Austin	27	4	+23	+575.0%
San Francisco	32	10	+22	+220.0%

Country	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
United States	1513	637	+876	+137.5%
CA (hybrid)	184	39	+145	+371.8%
India	122	31	+91	+293.6%
New York (hybrid)	52	4	+48	+1200.0%
Philippines	48	2	+46	+2300.0%

Showing first 5 of 10 rows.

Chart B: Top metros by net-new postings per 10k companies

Postings per 10k companies

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Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %	Active companies (180d)	Postings per 10k companies
San Carlos, California (United States)	59	3	+56	+1866.7%	1	590,000.0
Hybrid - San Francisco, California (United States)	60	13	+47	+361.5%	5	120,000.0
New York, New York (hybrid)	51	4	+47	+1175.0%	5	102,000.0
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%	14	43,571.4
Chicago, Illinois (United States)	62	10	+52	+520.0%	17	36,470.6
New York, New York (United States)	62	11	+51	+463.6%	42	14,761.9

Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %	Active companies (180d)	Postings per 10k companies
San Carlos, California (United States)	59	3	+56	+1866.7%	1	590,000.0
Hybrid - San Francisco, California (United States)	60	13	+47	+361.5%	5	120,000.0
New York, New York (hybrid)	51	4	+47	+1175.0%	5	102,000.0
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%	14	43,571.4
Chicago, Illinois (United States)	62	10	+52	+520.0%	17	36,470.6

Showing first 5 of 6 rows.

Chart C: Top metros by absolute net-new postings

Postings (last 30d)

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Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
Chicago, Illinois (United States)	62	10	+52	+520.0%
New York, New York (United States)	62	11	+51	+463.6%
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%
Hybrid - San Francisco, California (United States)	60	13	+47	+361.5%
San Carlos, California (United States)	59	3	+56	+1866.7%
New York, New York (hybrid)	51	4	+47	+1175.0%

Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
Chicago, Illinois (United States)	62	10	+52	+520.0%
New York, New York (United States)	62	11	+51	+463.6%
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%
Hybrid - San Francisco, California (United States)	60	13	+47	+361.5%
San Carlos, California (United States)	59	3	+56	+1866.7%

Showing first 5 of 6 rows.

Chart D: Hotspots vs cooling markets (delta vs prior 30d)

Delta postings

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Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
San Carlos, California (United States)	59	3	+56	+1866.7%
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%
Chicago, Illinois (United States)	62	10	+52	+520.0%
New York, New York (United States)	62	11	+51	+463.6%
New York, New York (hybrid)	51	4	+47	+1175.0%
London, London (hybrid)	12	26	-14	-53.9%

Metro	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %
San Carlos, California (United States)	59	3	+56	+1866.7%
San Francisco, San Francisco (CA (hybrid))	61	9	+52	+577.8%
Chicago, Illinois (United States)	62	10	+52	+520.0%
New York, New York (United States)	62	11	+51	+463.6%
New York, New York (hybrid)	51	4	+47	+1175.0%

Showing first 5 of 6 rows.

Chart E: Total postings trend (last 60 days)

Total postings

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Day (UTC)	Postings
2026-03-12	1565
2026-03-13	2994
2026-03-14	144
2026-03-15	2651
2026-03-16	2192
2026-03-17	2060
2026-03-18	3426
2026-03-19	3807
2026-03-20	3708
2026-03-21	2916
2026-03-22	121
2026-03-23	7647
2026-03-24	2967
2026-03-25	1358
2026-03-26	12964
2026-03-27	1781
2026-03-28	4078
2026-03-29	985
2026-03-30	7601
2026-03-31	3094
2026-04-01	13240
2026-04-02	1495
2026-04-03	1893
2026-04-04	1212
2026-04-05	11144
2026-04-06	2940
2026-04-07	10320
2026-04-08	2147
2026-04-09	1985
2026-04-10	3500
2026-04-11	403
2026-04-12	4855
2026-04-13	2605
2026-04-14	2182
2026-04-15	11446
2026-04-16	5529
2026-04-17	4995
2026-04-18	23091
2026-04-19	401
2026-04-20	8307
2026-04-21	2831
2026-04-22	7580
2026-04-23	3470
2026-04-24	3397
2026-04-25	1267
2026-04-26	1625
2026-04-27	6772
2026-04-28	3983
2026-04-29	7119
2026-04-30	5257
2026-05-01	4220
2026-05-02	67
2026-05-03	31375
2026-05-04	598
2026-05-05	3709
2026-05-06	16922
2026-05-07	20872
2026-05-08	74439
2026-05-09	44902
2026-05-10	39
2026-05-11	14387

Day (UTC)	Postings
2026-03-12	1565
2026-03-13	2994
2026-03-14	144
2026-03-15	2651
2026-03-16	2192

Showing first 5 of 61 rows.

Chart F: Top U.S. regions by normalized rate

Postings per 10k companies

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Region	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %	Active companies (180d)	Postings per 10k companies
California (United States)	397	163	+234	+143.6%	132	30,075.8
Illinois (United States)	85	14	+71	+507.1%	33	25,757.6
Massachusetts (United States)	87	29	+58	+200.0%	50	17,400.0
Texas (United States)	99	27	+72	+266.7%	64	15,468.8
Florida (United States)	51	17	+34	+200.0%	35	14,571.4
New York (United States)	123	39	+84	+215.4%	95	12,947.4

Region	Postings (last 30d)	Postings (prior 30d)	Delta	Delta %	Active companies (180d)	Postings per 10k companies
California (United States)	397	163	+234	+143.6%	132	30,075.8
Illinois (United States)	85	14	+71	+507.1%	33	25,757.6
Massachusetts (United States)	87	29	+58	+200.0%	50	17,400.0
Texas (United States)	99	27	+72	+266.7%	64	15,468.8
Florida (United States)	51	17	+34	+200.0%	35	14,571.4

Showing first 5 of 6 rows.

Remote-only roles snapshot

Remote-only postings are shown separately because they usually do not map cleanly to city-level metro buckets.

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Country	Remote-only postings (last 30d)
United States	14181
United Kingdom	637
Canada	606
India	442
Poland	323
Germany	299
Deutschland	285
Nederland	267
Mexico	263
Brazil	259

Country	Remote-only postings (last 30d)
United States	14181
United Kingdom	637
Canada	606
India	442
Poland	323

Showing first 5 of 10 rows.

If you're open to relocation/hybrid, focus on these 5 areas

San Carlos, California (United States): 59 postings in the last 30 days, +56 vs prior window, and 590,000.0 postings per 10k active companies.
Manila, Manila (Philippines (hybrid)): 37 postings in the last 30 days, +32 vs prior window, and 370,000.0 postings per 10k active companies.
Bangalore, Bangalore (India): 43 postings in the last 30 days, +34 vs prior window, and 215,000.0 postings per 10k active companies.
Noida, Uttar Pradesh (India): 27 postings in the last 30 days, +25 vs prior window, and 135,000.0 postings per 10k active companies.
Hybrid - San Francisco, California (United States): 60 postings in the last 30 days, +47 vs prior window, and 120,000.0 postings per 10k active companies.

Practical tips:

Create one alert per focus area with titles + local location terms (city, state, metro aliases).
Run a second broader alert for remote/hybrid to avoid missing adjacent opportunities.
Prioritize companies that posted repeatedly in the same area over the last month.
Rebalance your area list weekly using the risers/cooling table, not static assumptions.

Methodology and limitations

Methodology

Current window: 2026-04-11 to 2026-05-11 (UTC).

Prior window: 2026-03-12 to 2026-04-11 (UTC).

Net-new definition: Net-new postings by area = unique job postings in the current window minus unique job postings in the prior equal-length window.

Date fallback: 293,074 jobs (92.09%) used scannedAt fallback when postedAt was missing.

Coverage: parsed country 82.84%; parsed city 74.47%.

Normalization: Normalized postings per 10k = postings_last30 / distinct companies active in that area over the last 180 days * 10,000.

Geography logic: Country, region, and city are normalized before ranking. Country charts use country labels only; metro charts use City + Region + Country labels; region charts are U.S. states only to avoid mixed geography levels.

Remote handling: Metro and region rankings include only onsite/hybrid rows with concrete geography. Remote roles are reported separately by country.

Ranking thresholds: metros require at least 50 postings in the last 30 days; risers/cooling require at least 25 postings in either window.

Limitations

Location strings in ATS feeds are inconsistent, so some records remain unknown/unparsed.
Metro normalization controls for active-company presence in our dataset, not local labor force size.
Remote roles are split out because many rows use broad location labels (for example, Remote - United States).
This is a rolling 30-day snapshot and should be treated as directional, not permanent.
Unknown/unparsed non-remote rows this cycle: 272,759 (85.70%).

Start tracking these markets this week

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Remote Jobs Reality Check (Last 30 Days)

Where remote work is actually showing up right now—by industry, seniority, and geography.

Feb 28, 2026 · 2 min read · ATSRadar

#remote #job market #data #hiring trends

Remote hiring did not disappear, but it is no longer evenly distributed.

In this reality check, we analyze the last 30 days of ATSRadar job data to show where remote roles are concentrated by:

Industry
Seniority level
Country and U.S. state
Job family

When this report says job density, it means remote share (remote jobs / total jobs) in a category. We also show absolute remote-job volume so you can distinguish “high % but small sample” from “high volume and strong share.”

Key takeaways

Remote job density = remote share (remote jobs divided by total jobs). We also show remote-job counts so you can separate high share from low volume.
Overall remote share over the last 30 days: 13.22% (42070 remote jobs out of 318256).
Change vs prior 30-day window: -1.64 pp.
Highest-density industry above the volume threshold (50 jobs): Software/SaaS at 20.72%.
Most remote-heavy job family this month: Customer Success at 30.92%.
Largest geography bucket by total jobs: United States with 157327 jobs.

Data breakdown

How remote changed this month

Daily remote share ranged from 0.00% (2026-04-11) to 38.13% (2026-05-04). This helps separate temporary daily dips from sustained shifts.

Chart A: Daily remote share (%)

Remote share

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Day (UTC)	Total jobs	Remote jobs	Remote share
2026-04-11	14	0	0.00%
2026-04-12	4855	815	16.79%
2026-04-13	2605	359	13.78%
2026-04-14	2182	594	27.22%
2026-04-15	11446	1014	8.86%
2026-04-16	5529	1220	22.07%
2026-04-17	4995	945	18.92%
2026-04-18	23091	2586	11.20%
2026-04-19	401	63	15.71%
2026-04-20	8307	1695	20.40%
2026-04-21	2831	600	21.19%
2026-04-22	7580	839	11.07%
2026-04-23	3470	654	18.85%
2026-04-24	3397	779	22.93%
2026-04-25	1267	245	19.34%
2026-04-26	1625	130	8.00%
2026-04-27	6772	1086	16.04%
2026-04-28	3983	789	19.81%
2026-04-29	7119	929	13.05%
2026-04-30	5257	912	17.35%
2026-05-01	4220	584	13.84%
2026-05-02	67	18	26.87%
2026-05-03	31375	3960	12.62%
2026-05-04	598	228	38.13%
2026-05-05	3709	567	15.29%
2026-05-06	16922	1123	6.64%
2026-05-07	20872	3685	17.66%
2026-05-08	74439	7692	10.33%
2026-05-09	44902	5519	12.29%
2026-05-10	39	4	10.26%
2026-05-11	14387	2436	16.93%

Day (UTC)	Total jobs	Remote jobs	Remote share
2026-04-11	14	0	0.00%
2026-04-12	4855	815	16.79%
2026-04-13	2605	359	13.78%
2026-04-14	2182	594	27.22%
2026-04-15	11446	1014	8.86%

Showing first 5 of 31 rows.

Chart B: Daily mode mix (remote vs hybrid vs onsite)

RemoteHybridOnsite

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Day (UTC)	Remote	Hybrid	Onsite	Unknown mode
2026-04-11	0	0	0	14
2026-04-12	815	82	15	3943
2026-04-13	359	30	13	2203
2026-04-14	594	27	19	1542
2026-04-15	1014	112	42	10278
2026-04-16	1220	98	31	4180
2026-04-17	945	57	32	3961
2026-04-18	2586	108	206	20191
2026-04-19	63	2	0	336
2026-04-20	1695	106	26	6480
2026-04-21	600	35	17	2179
2026-04-22	839	66	40	6635
2026-04-23	654	51	20	2745
2026-04-24	779	44	23	2551
2026-04-25	245	15	3	1004
2026-04-26	130	9	5	1481
2026-04-27	1086	62	35	5589
2026-04-28	789	47	21	3126
2026-04-29	929	60	43	6087
2026-04-30	912	63	23	4259
2026-05-01	584	64	20	3552
2026-05-02	18	0	1	48
2026-05-03	3960	176	145	27094
2026-05-04	228	10	3	357
2026-05-05	567	36	15	3091
2026-05-06	1123	287	64	15448
2026-05-07	3685	328	72	16787
2026-05-08	7692	675	245	65827
2026-05-09	5519	786	138	38459
2026-05-10	4	0	0	35
2026-05-11	2436	351	58	11542

Day (UTC)	Remote	Hybrid	Onsite	Unknown mode
2026-04-11	0	0	0	14
2026-04-12	815	82	15	3943
2026-04-13	359	30	13	2203
2026-04-14	594	27	19	1542
2026-04-15	1014	112	42	10278

Showing first 5 of 31 rows.

Chart C: Top countries by remote share

Remote share

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Country	Total jobs	Remote jobs	Remote share	Change vs prior 30d
United States	157327	14009	8.90%	-3.59 pp
United Kingdom	7106	637	8.96%	-9.51 pp
Nederland	5786	267	4.61%	-1.03 pp
India	5052	442	8.75%	-1.73 pp
Canada	4688	606	12.93%	-12.14 pp
Deutschland	3959	285	7.20%	-15.12 pp
France	2661	220	8.27%	-4.43 pp
Germany	2633	299	11.36%	+0.64 pp
Singapore	1771	112	6.32%	-5.40 pp
Brazil	1770	259	14.63%	-0.30 pp
Spain	1551	193	12.44%	-4.74 pp
Netherlands	1523	98	6.43%	-3.90 pp

Country	Total jobs	Remote jobs	Remote share	Change vs prior 30d
United States	157327	14009	8.90%	-3.59 pp
United Kingdom	7106	637	8.96%	-9.51 pp
Nederland	5786	267	4.61%	-1.03 pp
India	5052	442	8.75%	-1.73 pp
Canada	4688	606	12.93%	-12.14 pp

Showing first 5 of 12 rows.

Chart D: U.S. states by remote share (minimum 50 jobs)

Remote share

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US state	Total jobs	Remote jobs	Remote share	Change vs prior 30d
California	23258	223	0.96%	-1.84 pp
New York	12380	150	1.21%	-2.58 pp
Texas	10269	151	1.47%	-2.70 pp
Massachusetts	5754	104	1.81%	-1.68 pp
Florida	5464	67	1.23%	-3.30 pp
Virginia	4716	40	0.85%	-2.16 pp
Washington	4113	71	1.73%	-3.92 pp
Illinois	3998	50	1.25%	-4.20 pp
Pennsylvania	3508	34	0.97%	+0.46 pp
Ohio	3397	19	0.56%	-1.55 pp
North Carolina	3276	55	1.68%	-3.31 pp
Maryland	3202	60	1.87%	-5.13 pp

US state	Total jobs	Remote jobs	Remote share	Change vs prior 30d
California	23258	223	0.96%	-1.84 pp
New York	12380	150	1.21%	-2.58 pp
Texas	10269	151	1.47%	-2.70 pp
Massachusetts	5754	104	1.81%	-1.68 pp
Florida	5464	67	1.23%	-3.30 pp

Showing first 5 of 12 rows.

Chart E: Industry remote density (top 10 by volume threshold)

Remote share

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Job density here means remote share (remote jobs divided by total jobs). Volume still matters, so each row also includes absolute remote-job counts.

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Industry	Total jobs	Remote jobs	Remote share	Change vs prior 30d
Software/SaaS	79700	16512	20.72%	-2.03 pp
Fintech	22103	4084	18.48%	-6.80 pp
Government/Nonprofit	2366	406	17.16%	-0.63 pp
Cybersecurity	14334	2248	15.68%	-3.05 pp
Healthcare	24967	3186	12.76%	-0.04 pp
Other/Unknown	47609	6071	12.75%	-2.48 pp
AI/ML	37869	4554	12.03%	-2.97 pp
Education	6414	632	9.85%	-12.90 pp
Energy/Climate	1820	100	5.49%	-0.44 pp
Marketplace/Logistics	73941	3907	5.28%	+0.60 pp
E-commerce/Consumer	7133	370	5.19%	-3.92 pp

Industry	Total jobs	Remote jobs	Remote share	Change vs prior 30d
Software/SaaS	79700	16512	20.72%	-2.03 pp
Fintech	22103	4084	18.48%	-6.80 pp
Government/Nonprofit	2366	406	17.16%	-0.63 pp
Cybersecurity	14334	2248	15.68%	-3.05 pp
Healthcare	24967	3186	12.76%	-0.04 pp

Showing first 5 of 11 rows.

Chart F: Job family remote share

Remote share

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Job family	Total jobs	Remote jobs	Remote share	Change vs prior 30d
Customer Success	2594	802	30.92%	-4.64 pp
Product	4099	1107	27.01%	-3.86 pp
Data	5445	1445	26.54%	+2.45 pp
Marketing	8401	2176	25.90%	+3.14 pp
Legal	4116	1011	24.56%	-10.59 pp
Design	5578	1261	22.61%	+3.31 pp
Engineering	41662	8168	19.61%	-1.48 pp
Sales	23853	4532	19.00%	+0.32 pp
Operations/RevOps	11183	2089	18.68%	-2.93 pp
Finance	6651	1143	17.19%	-11.00 pp
Security	4701	787	16.74%	+0.24 pp
HR/People	3026	463	15.30%	-4.35 pp
Other	196947	17086	8.68%	-0.66 pp

Job family	Total jobs	Remote jobs	Remote share	Change vs prior 30d
Customer Success	2594	802	30.92%	-4.64 pp
Product	4099	1107	27.01%	-3.86 pp
Data	5445	1445	26.54%	+2.45 pp
Marketing	8401	2176	25.90%	+3.14 pp
Legal	4116	1011	24.56%	-10.59 pp

Showing first 5 of 13 rows.

Unknown geography bucket: 54622 jobs (17.16%). Unknown/Unparsed U.S. state bucket: 33519 jobs (21.31% of U.S. jobs).

What this means if you want remote this month

If remote flexibility is your priority, optimize for job density + volume, not just total openings.

Use this shortlist process:

Prioritize industries with both high remote share and meaningful volume.
Prioritize countries/states with high remote share for your target families.
Target seniority bands that currently skew more remote.
Keep one broad alert for volume and one narrow alert for precision.
Refresh your alert filters weekly as remote concentration shifts.
Use location filters like Remote, United States, and top-performing states from this report.
Add family keywords to avoid irrelevant remote noise.
Track response rates by family and region, then rebalance.

What to do next: Pick one high-density, low-volume segment and one high-volume segment this week. Compare interview response rates after 7 days.

Example alert templates (copy/adapt)

Engineering (remote-first)

include titles: software engineer, backend, frontend, full stack, platform, sre
include keywords: remote, distributed, anywhere
exclude keywords: onsite only, in office

Data (remote)

include titles: data engineer, data scientist, analytics engineer, ml engineer
include keywords: remote, python, sql

Product (remote)

include titles: product manager, product owner, group product manager
include keywords: remote, distributed, b2b saas

Design (remote)

include titles: product designer, ux designer, ui designer
include keywords: remote, figma

Marketing / Growth (remote)

include titles: growth marketing, performance marketing, demand generation
include keywords: remote, seo, lifecycle

Methodology

Window: 30 days ending 2026-05-11T08:12:47.823Z (UTC).

Job date logic: Jobs are included when postedAt is in the window. If postedAt is missing, scannedAt is used as fallback.

Fallback impact: 293074 jobs (92.09%) used scannedAt fallback.

Remote classification: Work mode uses jobs.remoteFlag first, then text rules on title/location/description: remote keywords (remote/work from home/wfh/anywhere/distributed), hybrid keywords, then onsite keywords; otherwise Unknown.

Geography extraction: Country and U.S. state are parsed from normalized location text. Unknown buckets are tracked in data-coverage summary metrics, not top rankings.

Industry inference: Industry uses company metadata when available, then category/department mapping hints, then keyword inference from company/title/description.

Seniority inference: Seniority is inferred from title/seniority text with deterministic keyword mapping (Intern, Junior, Mid, Senior, Staff, Principal, Lead, Manager, Senior Manager, Director, VP, C-level).

Job family inference: Job family is inferred from title + category/department/function hints (Engineering, Data, Product, Design, Sales, Marketing, Customer Success, Finance, HR/People, Operations/RevOps, Security, Legal, Other).

State table threshold: U.S. states require at least 50 jobs in-window (Unknown/Unparsed always shown).

Limitations

ATS location strings are inconsistent, so country/state parsing can miss edge cases.
Remote, hybrid, and onsite classification is rule-based and may misclassify ambiguous wording.
Industry, family, and seniority can be inferred when source fields are missing, which introduces uncertainty.
This is a 30-day snapshot and should be treated as directional, not permanent.

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