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: 13.22% (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
38.1% 28.6% 19.1% 9.5% 0.0% 04-1104-1704-2304-2905-0505-11

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Day (UTC)Total jobsRemote jobsRemote share
2026-04-111400.00%
2026-04-12485581516.79%
2026-04-13260535913.78%
2026-04-14218259427.22%
2026-04-151144610148.86%
2026-04-165529122022.07%
2026-04-17499594518.92%
2026-04-1823091258611.20%
2026-04-194016315.71%
2026-04-208307169520.40%
2026-04-21283160021.19%
2026-04-22758083911.07%
2026-04-23347065418.85%
2026-04-24339777922.93%
2026-04-25126724519.34%
2026-04-2616251308.00%
2026-04-276772108616.04%
2026-04-28398378919.81%
2026-04-29711992913.05%
2026-04-30525791217.35%
2026-05-01422058413.84%
2026-05-02671826.87%
2026-05-0331375396012.62%
2026-05-0459822838.13%
2026-05-05370956715.29%
2026-05-061692211236.64%
2026-05-0720872368517.66%
2026-05-0874439769210.33%
2026-05-0944902551912.29%
2026-05-1039410.26%
2026-05-1114387243616.93%
Day (UTC)Total jobsRemote jobsRemote share
2026-04-111400.00%
2026-04-12485581516.79%
2026-04-13260535913.78%
2026-04-14218259427.22%
2026-04-151144610148.86%

Showing first 5 of 31 rows.

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

RemoteHybridOnsite
8,612 6,459 4,306 2,153 0 04-1104-1704-2304-2905-0505-11

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Day (UTC)RemoteHybridOnsiteUnknown mode
2026-04-1100014
2026-04-1281582153943
2026-04-1335930132203
2026-04-1459427191542
2026-04-1510141124210278
2026-04-16122098314180
2026-04-1794557323961
2026-04-18258610820620191
2026-04-196320336
2026-04-201695106266480
2026-04-2160035172179
2026-04-2283966406635
2026-04-2365451202745
2026-04-2477944232551
2026-04-252451531004
2026-04-26130951481
2026-04-27108662355589
2026-04-2878947213126
2026-04-2992960436087
2026-04-3091263234259
2026-05-0158464203552
2026-05-02180148
2026-05-03396017614527094
2026-05-04228103357
2026-05-0556736153091
2026-05-0611232876415448
2026-05-0736853287216787
2026-05-08769267524565827
2026-05-09551978613838459
2026-05-1040035
2026-05-1124363515811542
Day (UTC)RemoteHybridOnsiteUnknown mode
2026-04-1100014
2026-04-1281582153943
2026-04-1335930132203
2026-04-1459427191542
2026-04-1510141124210278

Showing first 5 of 31 rows.

Chart C: Top countries by remote share

Remote share
14.6% 11.0% 7.3% 3.7% 0.0% BrazilCanadaGermanyUnited KingdomUnited StatesIndiaFranceDeutschlandSingaporeNederland

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CountryTotal jobsRemote jobsRemote shareChange vs prior 30d
United States157327140098.90%-3.59 pp
United Kingdom71066378.96%-9.51 pp
Nederland57862674.61%-1.03 pp
India50524428.75%-1.73 pp
Canada468860612.93%-12.14 pp
Deutschland39592857.20%-15.12 pp
France26612208.27%-4.43 pp
Germany263329911.36%+0.64 pp
Singapore17711126.32%-5.40 pp
Brazil177025914.63%-0.30 pp
Spain155119312.44%-4.74 pp
Netherlands1523986.43%-3.90 pp
CountryTotal jobsRemote jobsRemote shareChange vs prior 30d
United States157327140098.90%-3.59 pp
United Kingdom71066378.96%-9.51 pp
Nederland57862674.61%-1.03 pp
India50524428.75%-1.73 pp
Canada468860612.93%-12.14 pp

Showing first 5 of 12 rows.

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

Remote share
1.8% 1.4% 0.9% 0.5% 0.0% MassachusettsWashingtonTexasIllinoisFloridaNew YorkPennsylvaniaCaliforniaVirginiaOhio

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US stateTotal jobsRemote jobsRemote shareChange vs prior 30d
California232582230.96%-1.84 pp
New York123801501.21%-2.58 pp
Texas102691511.47%-2.70 pp
Massachusetts57541041.81%-1.68 pp
Florida5464671.23%-3.30 pp
Virginia4716400.85%-2.16 pp
Washington4113711.73%-3.92 pp
Illinois3998501.25%-4.20 pp
Pennsylvania3508340.97%+0.46 pp
Ohio3397190.56%-1.55 pp
North Carolina3276551.68%-3.31 pp
Maryland3202601.87%-5.13 pp
US stateTotal jobsRemote jobsRemote shareChange vs prior 30d
California232582230.96%-1.84 pp
New York123801501.21%-2.58 pp
Texas102691511.47%-2.70 pp
Massachusetts57541041.81%-1.68 pp
Florida5464671.23%-3.30 pp

Showing first 5 of 12 rows.

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

Remote share
20.7% 15.5% 10.4% 5.2% 0.0% Software/SaaSFintechGovernment/...CybersecurityHealthcareOther/UnknownAI/MLEducationEnergy/ClimateMarketplace...

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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
Software/SaaS797001651220.72%-2.03 pp
Fintech22103408418.48%-6.80 pp
Government/Nonprofit236640617.16%-0.63 pp
Cybersecurity14334224815.68%-3.05 pp
Healthcare24967318612.76%-0.04 pp
Other/Unknown47609607112.75%-2.48 pp
AI/ML37869455412.03%-2.97 pp
Education64146329.85%-12.90 pp
Energy/Climate18201005.49%-0.44 pp
Marketplace/Logistics7394139075.28%+0.60 pp
E-commerce/Consumer71333705.19%-3.92 pp
IndustryTotal jobsRemote jobsRemote shareChange vs prior 30d
Software/SaaS797001651220.72%-2.03 pp
Fintech22103408418.48%-6.80 pp
Government/Nonprofit236640617.16%-0.63 pp
Cybersecurity14334224815.68%-3.05 pp
Healthcare24967318612.76%-0.04 pp

Showing first 5 of 11 rows.

Chart F: Job family remote share

Remote share
30.9% 23.2% 15.5% 7.7% 0.0% Customer Su...ProductDataMarketingLegalDesignEngineeringSalesOperations/...Finance

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Job familyTotal jobsRemote jobsRemote shareChange vs prior 30d
Customer Success259480230.92%-4.64 pp
Product4099110727.01%-3.86 pp
Data5445144526.54%+2.45 pp
Marketing8401217625.90%+3.14 pp
Legal4116101124.56%-10.59 pp
Design5578126122.61%+3.31 pp
Engineering41662816819.61%-1.48 pp
Sales23853453219.00%+0.32 pp
Operations/RevOps11183208918.68%-2.93 pp
Finance6651114317.19%-11.00 pp
Security470178716.74%+0.24 pp
HR/People302646315.30%-4.35 pp
Other196947170868.68%-0.66 pp
Job familyTotal jobsRemote jobsRemote shareChange vs prior 30d
Customer Success259480230.92%-4.64 pp
Product4099110727.01%-3.86 pp
Data5445144526.54%+2.45 pp
Marketing8401217625.90%+3.14 pp
Legal4116101124.56%-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:

  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 2026-05-11T08:12:47.823Z (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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