quantitative research jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, quantitative research appears in 324 job postings indexed by Skillenai over the past 90 days — UX Researcher has the most postings mentioning quantitative research, with demand share up 10.4% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
324
Demand vs prior month
up 10.4% vs the prior 4 weeks
Top role · 19.8% of skill postings
Top hiring metro
New York City

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Frequently asked questions about quantitative research

+Is quantitative research in demand in 2026?

Yes. quantitative research appears in 324 job postings indexed by Skillenai over the 90 days ending 2026-09-30. UX Researcher accounts for the most postings mentioning quantitative research (19.8% of all postings mentioning quantitative research).

+What jobs require quantitative research?

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 quantitative research are UX Researcher (30.5% of that role’s postings mention quantitative research), Design Program Manager (14.3% of that role’s postings mention quantitative research), Quantitative Researcher (6.9% of that role’s postings mention quantitative research).

+What skills are commonly paired with quantitative research?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), quantitative research most often appears alongside Qualitative research, user research, Data analysis, UX research, usability testing.

+Where is quantitative research most in demand?

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

+How can I keep up with new quantitative research content and jobs?

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

+Which skills come before and after quantitative research?

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 quantitative research — last 90 days

Career paths around quantitative research

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before quantitative research

Before quantitative researchusability testing → quantitative research: 1 observed employer moves with this skill pairevidence-based decision-making → quantitative research: 1 observed employer moves with this skill pairpatient records → quantitative research: 1 observed employer moves with this skill pairresponsive high-fidelity prototype → quantitative research: 1 observed employer moves with this skill pairmarketing analytics → quantitative research: 1 observed employer moves with this skill pairMYSQL → quantitative research: 1 observed employer moves with this skill pairCRM → quantitative research: 1 observed employer moves with this skill pairROI models → quantitative research: 1 observed employer moves with this skill pairquantitativeresearchusability testing: 1 movesusability testing1 movesevidence-based decision-making: 1 movesevidence-baseddecision-making1 movespatient records: 1 movespatient records1 movesresponsive high-fidelity prototype: 1 movesresponsivehigh-fidelityprototype1 movesmarketing analytics: 1 movesmarketinganalytics1 movesMYSQL: 1 movesMYSQL1 movesCRM: 1 movesCRM1 movesROI models: 1 movesROI models1 moves

Skills after quantitative research

After quantitative researchquantitative research → sql: 2 observed employer moves with this skill pairquantitative research → business systems analysis: 1 observed employer moves with this skill pairquantitative research → scikit-learn: 1 observed employer moves with this skill pairquantitative research → Meta descriptions: 1 observed employer moves with this skill pairquantitative research → click-through rate: 1 observed employer moves with this skill pairquantitative research → Logentries: 1 observed employer moves with this skill pairquantitative research → conversion rate: 1 observed employer moves with this skill pairquantitative research → data cleansing: 1 observed employer moves with this skill pairquantitativeresearchsql: 2 movessql2 movesbusiness systems analysis: 1 movesbusiness systemsanalysis1 movesscikit-learn: 1 movesscikit-learn1 movesMeta descriptions: 1 movesMeta descriptions1 movesclick-through rate: 1 movesclick-through rate1 movesLogentries: 1 movesLogentries1 movesconversion rate: 1 movesconversion rate1 movesdata cleansing: 1 movesdata cleansing1 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: usability testing1
Before: evidence-based decision-making1
Before: patient records1
Before: responsive high-fidelity prototype1
Before: marketing analytics1
Before: MYSQL1
Before: CRM1
Before: ROI models1
After: sql2
After: business systems analysis1
After: scikit-learn1
After: Meta descriptions1
After: click-through rate1
After: Logentries1
After: conversion rate1
After: data cleansing1

Roles most likely to require quantitative research

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

RolePostings mentioning skill% of role postings mentioning skill
UX Researcher6430.5%
Design Program Manager314.3%
Quantitative Researcher126.9%
Growth Product Manager46.7%
Quantitative Trader34.5%
AI Product Designer14.0%
Marketing Analytics Director13.7%
Business Intelligence Director12.5%
UX Designer112.1%
Researcher11.6%

Roles with the most quantitative research postings

RolePostings mentioning skillShare of skill postings
UX Researcher6419.8%
Product Manager5817.9%
Product Designer3711.4%
Quantitative Researcher123.7%
UX Designer113.4%
Data Scientist61.9%
Data Analyst41.2%
Growth Product Manager41.2%
Quantitative Trading Intern41.2%
Analytics Manager30.9%

Top companies posting jobs requiring quantitative research

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

Top companies posting jobs requiring quantitative research
CompanyPostings · 90 days
Intuitive15
LBG8
Belvedere Trading5
AbbVie5
Reonic4
PointClickCare4
Babylist4
Agoda4
BlackRock4
The New York Times3

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 quantitative research

NamePostingsShare
New York City268.0%
London195.9%
Sunnyvale144.3%
San Francisco103.1%
Berlin82.5%
Chicago82.5%
Amsterdam51.5%
Bangkok41.2%
Barcelona41.2%

Skills commonly paired with quantitative research

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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 quantitative research by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s quantitative research postings by all quantitative research 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: 0.1% to 0.1%. 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 2,595 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
8bea115b22f1f057
data_as_of
2026-09-30
window_days
90
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Compiled by Jared Rand · Data sourced from the Skillenai labor market index