data collection jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, data collection appears in 762 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning data collection, with demand share down 6.0% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
762
Demand vs prior month
down 6.0% vs the prior 4 weeks
Top role · 6.2% of skill postings
Top hiring metro
San Francisco

Which roles want data collection?

Upload your resume and Skillenai will show which roles your data collection experience fits, which skills you already cover, and what is missing.

Prepare to discuss data collection in your interview

We’re building mock interviews informed by job postings and career profiles, to help you explain how you’ve used data collection.

Join the mock interview waitlist →AI or human interviews. Coming soon.

Frequently asked questions about data collection

+Is data collection in demand in 2026?

Yes. data collection appears in 762 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning data collection (6.2% of all postings mentioning data collection).

+What jobs require data collection?

According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning data collection are Machine Learning Manager (12.0% of that role’s postings mention data collection), Clinical Research Scientist (10.0% of that role’s postings mention data collection), Data Analytics Analyst (10.0% of that role’s postings mention data collection).

+What skills are commonly paired with data collection?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), data collection most often appears alongside Data analysis, Python, machine learning, SQL, data visualization.

+Where is data collection most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring data collection are San Francisco, New York City, Mountain View, London, Sunnyvale, according to the Skillenai jobs index.

+How can I keep up with new data collection content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning data collection alongside the jobs index. You can subscribe to a daily email digest of new data collection content from your Skillenai account.

+Which skills come before and after data collection?

The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.

Weekly indexed postings requiring data collection — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around data collection

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data collection

Before data collectionpython → data collection: 16 observed employer moves with this skill pairdata analysis → data collection: 12 observed employer moves with this skill pairTableau → data collection: 11 observed employer moves with this skill pairsql → data collection: 10 observed employer moves with this skill pairExcel → data collection: 8 observed employer moves with this skill pairscikit-learn → data collection: 6 observed employer moves with this skill pairSurveys → data collection: 5 observed employer moves with this skill pairanalytics → data collection: 5 observed employer moves with this skill pairdatacollectionpython: 16 movespython16 movesdata analysis: 12 movesdata analysis12 movesTableau: 11 movesTableau11 movessql: 10 movessql10 movesExcel: 8 movesExcel8 movesscikit-learn: 6 movesscikit-learn6 movesSurveys: 5 movesSurveys5 movesanalytics: 5 movesanalytics5 moves

Skills after data collection

After data collectiondata collection → sql: 14 observed employer moves with this skill pairdata collection → Tableau: 14 observed employer moves with this skill pairdata collection → python: 12 observed employer moves with this skill pairdata collection → Power BI: 10 observed employer moves with this skill pairdata collection → Excel: 8 observed employer moves with this skill pairdata collection → dashboards: 5 observed employer moves with this skill pairdata collection → Data Visualization: 5 observed employer moves with this skill pairdata collection → data analysis: 5 observed employer moves with this skill pairdatacollectionsql: 14 movessql14 movesTableau: 14 movesTableau14 movespython: 12 movespython12 movesPower BI: 10 movesPower BI10 movesExcel: 8 movesExcel8 movesdashboards: 5 movesdashboards5 movesData Visualization: 5 movesData Visualization5 movesdata analysis: 5 movesdata analysis5 moves
How to read this chart · view counts

Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.

The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.

Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.

Observed connections and move counts
ConnectionMoves
Before: python16
Before: data analysis12
Before: Tableau11
Before: sql10
Before: Excel8
Before: scikit-learn6
Before: Surveys5
Before: analytics5
After: sql14
After: Tableau14
After: python12
After: Power BI10
After: Excel8
After: dashboards5
After: Data Visualization5
After: data analysis5

Roles most likely to require data collection

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Machine Learning Manager312.0%
Clinical Research Scientist210.0%
Data Analytics Analyst210.0%
Research Program Manager28.7%
AI Intern28.3%
Flight Test Engineer67.4%
Analytics Intern27.1%
Analytics Director65.5%
Perception Engineer15.0%
Researcher34.8%

Roles with the most data collection postings

RolePostings mentioning skillShare of skill postings
Data Scientist476.2%
Data Analyst425.5%
Product Manager334.3%
Program Manager303.9%
Software Engineer303.9%
Systems Engineer263.4%
Research Scientist192.5%
Business Analyst182.4%
Test Engineer162.1%
Machine Learning Engineer121.6%

Top companies posting jobs requiring data collection

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring data collection
CompanyPostings · 90 days
Rws17
OpenBrain14
Globalpr10
ProSidian Consulting10
Waymo9
Anthropic7
NielsenIQ7
General Motors7
Northrop Grumman7
NVIDIA7

Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.

Top metros hiring for data collection

NamePostingsShare
San Francisco374.9%
New York City192.5%
Mountain View172.2%
London152.0%
Sunnyvale111.4%
Austin101.3%
Paris101.3%
Singapore101.3%
Arlington81.0%

Skills commonly paired with data collection

Get a daily email digest of new data collection content

Skillenai indexes news articles, blog posts, and research papers that mention data collection. Click below and we'll open a pre-filled daily digest — change the cadence to hourly or weekly if you prefer, then save. Free account required (~30 seconds).

Explore related pages

How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning data collection by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data collection postings by all data collection postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.3% to 0.3%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,596 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.

source
Skillenai jobs index, deduplicated daily
entity_id
eeecad1090a00a76
data_as_of
2026-09-30
window_days
90
Hiring engineers who use data collection?

The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.

Skillenai for recruiters →
Compiled by Jared Rand · Data sourced from the Skillenai labor market index