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:

  1. Industry
  2. Seniority level
  3. Country and U.S. state
  4. 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: 13.59% (37030 remote jobs out of 272545).
  • Change vs prior 30-day window: -9.51 pp.
  • Highest-density industry above the volume threshold (50 jobs): Education at 21.51%.
  • Most remote-heavy job family this month: Customer Success at 32.93%.
  • Largest geography bucket by total jobs: United States with 120198 jobs.

Data breakdown

How remote changed this month

Daily remote share ranged from 1.72% (2026-03-15) to 47.86% (2026-03-22). This helps separate temporary daily dips from sustained shifts.

Chart A: Daily remote share (%)

Remote share
47.9% 35.9% 23.9% 12.0% 0.0% 02-2503-0303-0903-1503-2103-27

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Day (UTC)Total jobsRemote jobsRemote share
2026-02-25210231314.89%
2026-02-26399975618.90%
2026-02-27382264616.90%
2026-02-281554976.24%
2026-03-011162605.16%
2026-03-0269006008.70%
2026-03-03353578822.29%
2026-03-04484361912.78%
2026-03-05474369014.55%
2026-03-06691171810.39%
2026-03-073877018.09%
2026-03-08511203.91%
2026-03-0962855188.24%
2026-03-10255244817.55%
2026-03-11259949619.08%
2026-03-12256551720.16%
2026-03-13317852116.39%
2026-03-141803921.67%
2026-03-152783481.72%
2026-03-16227839517.34%
2026-03-17218946221.11%
2026-03-18363368718.91%
2026-03-1944443998.98%
2026-03-20505664812.82%
2026-03-21329045113.71%
2026-03-221406747.86%
2026-03-238395132015.72%
2026-03-24325351415.80%
2026-03-25141540628.69%
2026-03-261778342371513.34%
2026-03-277228.57%
Day (UTC)Total jobsRemote jobsRemote share
2026-02-25210231314.89%
2026-02-26399975618.90%
2026-02-27382264616.90%
2026-02-281554976.24%
2026-03-011162605.16%

Showing first 5 of 31 rows.

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

RemoteHybridOnsite
26,991 20,243 13,496 6,748 0 02-2503-0303-0903-1503-2103-27

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Day (UTC)RemoteHybridOnsiteUnknown mode
2026-02-2531330181741
2026-02-2675637213185
2026-02-2764663163097
2026-02-28974941404
2026-03-0160111100
2026-03-0260067446189
2026-03-03788128172602
2026-03-0461960184146
2026-03-0569078253950
2026-03-0671864416088
2026-03-077062309
2026-03-082011489
2026-03-0951840195708
2026-03-1044844282032
2026-03-1149627262050
2026-03-1251737121999
2026-03-1352125232609
2026-03-143944133
2026-03-154810122713
2026-03-1639519171847
2026-03-1746232171678
2026-03-1868761142871
2026-03-1939928273990
2026-03-2064845314332
2026-03-21451104192716
2026-03-22672071
2026-03-231320118616896
2026-03-2451449252665
2026-03-254061712980
2026-03-26237152531745150843
2026-03-272005
Day (UTC)RemoteHybridOnsiteUnknown mode
2026-02-2531330181741
2026-02-2675637213185
2026-02-2764663163097
2026-02-28974941404
2026-03-0160111100

Showing first 5 of 31 rows.

Chart C: Top countries by remote share

Remote share
18.6% 13.9% 9.3% 4.6% 0.0% CanadaBrazilDeutschlandUnited KingdomUnited StatesGermanyFranceIndiaSingaporeNederland

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CountryTotal jobsRemote jobsRemote shareChange vs prior 30d
United States1201981329111.06%-7.36 pp
Nederland60462764.57%+4.57 pp
United Kingdom583564811.11%-14.65 pp
Deutschland456556512.38%+12.38 pp
India44493838.61%-11.04 pp
Canada284352818.57%-18.35 pp
France25962429.32%+0.44 pp
Germany253327610.90%-2.06 pp
Singapore1665855.11%-2.09 pp
Brazil164523214.10%-11.74 pp
Spain157520713.14%-17.25 pp
Netherlands15091167.69%-7.44 pp
CountryTotal jobsRemote jobsRemote shareChange vs prior 30d
United States1201981329111.06%-7.36 pp
Nederland60462764.57%+4.57 pp
United Kingdom583564811.11%-14.65 pp
Deutschland456556512.38%+12.38 pp
India44493838.61%-11.04 pp

Showing first 5 of 12 rows.

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

Remote share
3.6% 2.7% 1.8% 0.9% 0.0% MarylandFloridaIllinoisTexasWashingtonMassachusettsVirginiaNew YorkCaliforniaPennsylvania

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US stateTotal jobsRemote jobsRemote shareChange vs prior 30d
California180302861.59%-3.60 pp
New York93951902.02%-4.80 pp
Texas68501682.45%-5.80 pp
Massachusetts44011002.27%-3.73 pp
Florida37361173.13%-7.59 pp
Virginia3306692.09%-1.97 pp
Illinois3019882.91%-7.43 pp
Washington3006712.36%-11.48 pp
Maryland28311013.57%-8.36 pp
Pennsylvania2489281.12%+0.26 pp
Ohio2273421.85%-2.52 pp
North Carolina2215532.39%-4.28 pp
US stateTotal jobsRemote jobsRemote shareChange vs prior 30d
California180302861.59%-3.60 pp
New York93951902.02%-4.80 pp
Texas68501682.45%-5.80 pp
Massachusetts44011002.27%-3.73 pp
Florida37361173.13%-7.59 pp

Showing first 5 of 12 rows.

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

Remote share
21.5% 16.1% 10.8% 5.4% 0.0% EducationFintechSoftware/SaaSCybersecurityOther/UnknownHealthcareGovernment/...AI/MLE-commerce/...Energy/Climate

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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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IndustryTotal jobsRemote jobsRemote shareChange vs prior 30d
Education5057108821.51%-14.71 pp
Fintech19251408421.21%-1.98 pp
Software/SaaS735501545021.01%-5.60 pp
Cybersecurity11894207117.41%-11.30 pp
Other/Unknown20075291714.53%-19.84 pp
Healthcare22219286012.87%-1.74 pp
Government/Nonprofit375740010.65%-14.43 pp
AI/ML39773417610.50%-11.53 pp
E-commerce/Consumer59573976.66%-0.27 pp
Energy/Climate1694885.19%-2.59 pp
Marketplace/Logistics6931834995.05%-6.91 pp
IndustryTotal jobsRemote jobsRemote shareChange vs prior 30d
Education5057108821.51%-14.71 pp
Fintech19251408421.21%-1.98 pp
Software/SaaS735501545021.01%-5.60 pp
Cybersecurity11894207117.41%-11.30 pp
Other/Unknown20075291714.53%-19.84 pp

Showing first 5 of 11 rows.

Chart F: Job family remote share

Remote share
32.9% 24.7% 16.5% 8.2% 0.0% Customer Su...LegalProductDataMarketingFinanceDesignEngineeringOperations/...Sales

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Job familyTotal jobsRemote jobsRemote shareChange vs prior 30d
Customer Success233877032.93%-15.17 pp
Legal3887109128.07%+0.65 pp
Product3800105427.74%-6.78 pp
Data5211127724.51%-10.60 pp
Marketing8687189921.86%-6.43 pp
Finance6573138321.04%-0.23 pp
Design5853118420.23%-4.49 pp
Engineering38944739418.99%-8.92 pp
Operations/RevOps11796223518.95%-4.51 pp
Sales20564386918.81%-9.85 pp
Security5698105418.50%-2.04 pp
HR/People284843615.31%-12.26 pp
Other156346133848.56%-6.69 pp
Job familyTotal jobsRemote jobsRemote shareChange vs prior 30d
Customer Success233877032.93%-15.17 pp
Legal3887109128.07%+0.65 pp
Product3800105427.74%-6.78 pp
Data5211127724.51%-10.60 pp
Marketing8687189921.86%-6.43 pp

Showing first 5 of 13 rows.

Unknown geography bucket: 54097 jobs (19.85%). Unknown/Unparsed U.S. state bucket: 28935 jobs (24.07% 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:

  1. Prioritize industries with both high remote share and meaningful volume.
  2. Prioritize countries/states with high remote share for your target families.
  3. Target seniority bands that currently skew more remote.
  4. Keep one broad alert for volume and one narrow alert for precision.
  5. Refresh your alert filters weekly as remote concentration shifts.
  6. Use location filters like Remote, United States, and top-performing states from this report.
  7. Add family keywords to avoid irrelevant remote noise.
  8. 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 2026-03-27T07:48:52.355Z (UTC).

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

Fallback impact: 202126 jobs (74.16%) 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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