experiment design jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, experiment design appears in 633 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning experiment design, with demand share up 4.1% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
633
Demand vs prior month
up 4.1% vs the prior 4 weeks
Top role · 24.3% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about experiment design

+Is experiment design in demand in 2026?

Yes. experiment design appears in 633 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Product Manager accounts for the most postings mentioning experiment design (24.3% of all postings mentioning experiment design).

+What jobs require experiment design?

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 experiment design are Marketing Analytics Lead (14.3% of that role’s postings mention experiment design), Quantitative Researcher (8.6% of that role’s postings mention experiment design), Growth Product Manager (8.3% of that role’s postings mention experiment design).

+What skills are commonly paired with experiment design?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), experiment design most often appears alongside Python, A/B testing, SQL, Data analysis, machine learning.

+Where is experiment design most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring experiment design are San Francisco, New York City, London, Singapore, Berlin, according to the Skillenai jobs index.

+How can I keep up with new experiment design content and jobs?

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

+Which skills come before and after experiment design?

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 experiment design — last 90 days

Salary distribution

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

Career paths around experiment design

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before experiment design

Before experiment designpython → experiment design: 2 observed employer moves with this skill pairR → experiment design: 2 observed employer moves with this skill pairvisualizations → experiment design: 1 observed employer moves with this skill pairpredictive analytics → experiment design: 1 observed employer moves with this skill pairSPSS → experiment design: 1 observed employer moves with this skill pairStatistical testing → experiment design: 1 observed employer moves with this skill pairUS Census → experiment design: 1 observed employer moves with this skill paircriterion learning → experiment design: 1 observed employer moves with this skill pairexperimentdesignpython: 2 movespython2 movesR: 2 movesR2 movesvisualizations: 1 movesvisualizations1 movespredictive analytics: 1 movespredictiveanalytics1 movesSPSS: 1 movesSPSS1 movesStatistical testing: 1 movesStatisticaltesting1 movesUS Census: 1 movesUS Census1 movescriterion learning: 1 movescriterion learning1 moves

Skills after experiment design

After experiment designexperiment design → python: 2 observed employer moves with this skill pairexperiment design → real-time visibility: 1 observed employer moves with this skill pairexperiment design → ETL: 1 observed employer moves with this skill pairexperiment design → eye movement patterns: 1 observed employer moves with this skill pairexperiment design → Power BI: 1 observed employer moves with this skill pairexperiment design → machine learning libraries: 1 observed employer moves with this skill pairexperiment design → time series analysis: 1 observed employer moves with this skill pairexperiment design → data visualizations: 1 observed employer moves with this skill pairexperimentdesignpython: 2 movespython2 movesreal-time visibility: 1 movesreal-timevisibility1 movesETL: 1 movesETL1 moveseye movement patterns: 1 moveseye movementpatterns1 movesPower BI: 1 movesPower BI1 movesmachine learning libraries: 1 movesmachine learninglibraries1 movestime series analysis: 1 movestime seriesanalysis1 movesdata visualizations: 1 movesdatavisualizations1 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: python2
Before: R2
Before: visualizations1
Before: predictive analytics1
Before: SPSS1
Before: Statistical testing1
Before: US Census1
Before: criterion learning1
After: python2
After: real-time visibility1
After: ETL1
After: eye movement patterns1
After: Power BI1
After: machine learning libraries1
After: time series analysis1
After: data visualizations1

Roles most likely to require experiment design

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

RolePostings mentioning skill% of role postings mentioning skill
Marketing Analytics Lead314.3%
Quantitative Researcher158.6%
Growth Product Manager58.3%
Product Data Scientist57.9%
Safeguards Enforcement Analyst27.4%
Product Analytics Manager26.2%
Machine Learning Research Engineer25.9%
Product Analyst125.0%
Applied ML Engineer14.8%
Credit Risk Manager14.5%

Roles with the most experiment design postings

RolePostings mentioning skillShare of skill postings
Product Manager15424.3%
Data Scientist8813.9%
Machine Learning Engineer426.6%
Software Engineer253.9%
Data Analyst162.5%
Research Scientist162.5%
Product Designer152.4%
Quantitative Researcher152.4%
Product Analyst121.9%
Engineering Manager111.7%

Top companies posting jobs requiring experiment design

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

Top companies posting jobs requiring experiment design
CompanyPostings · 90 days
Waymo20
Jane Street13
Grab13
Pinterest12
CLERA9
Google8
OpenAI7
Powerdigitalmarketing7
Doctolib6
Bjakcareer6

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 experiment design

NamePostingsShare
San Francisco6610.4%
New York City436.8%
London365.7%
Singapore111.7%
Berlin101.6%
Boston91.4%
Seattle91.4%
Mountain View81.3%
Toronto81.3%

Skills commonly paired with experiment design

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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 experiment design by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s experiment design postings by all experiment design 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
2e9911d107f0e1d2
data_as_of
2026-09-30
window_days
90
Hiring engineers who use experiment design?

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.

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