econometrics jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, econometrics appears in 241 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning econometrics, with demand share up 15.5% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want econometrics?
Upload your resume and Skillenai will show which roles your econometrics experience fits, which skills you already cover, and what is missing.
Frequently asked questions about econometrics
+Is econometrics in demand in 2026?
Yes. econometrics appears in 241 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Data Scientist accounts for the most postings mentioning econometrics (26.1% of all postings mentioning econometrics).
+What jobs require econometrics?
According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning econometrics are Economist (43.5% of that role’s postings mention econometrics), Data Science Consultant (16.2% of that role’s postings mention econometrics), Senior Data Scientist (11.1% of that role’s postings mention econometrics).
+What skills are commonly paired with econometrics?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), econometrics most often appears alongside Python, SQL, Machine Learning, R, causal inference.
+Where is econometrics most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring econometrics are San Francisco, New York City, London, McLean, Singapore, according to the Skillenai jobs index.
+How can I keep up with new econometrics content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning econometrics alongside the jobs index. You can subscribe to a daily email digest of new econometrics content from your Skillenai account.
+Which skills come before and after econometrics?
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 econometrics — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around econometrics
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before econometrics
Skills after econometrics
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.
| Connection | Moves |
|---|---|
| Before: sql | 2 |
| Before: econometric models | 2 |
| Before: DCF | 1 |
| Before: LBO | 1 |
| Before: ETL pipelines | 1 |
| Before: credit risk strategies | 1 |
| Before: Clickhouse | 1 |
| Before: automation | 1 |
| After: Data Visualization | 2 |
| After: python | 2 |
| After: boosting | 1 |
| After: data cleansing | 1 |
| After: QA QC | 1 |
| After: Bagging | 1 |
| After: Salesforce | 1 |
| After: full-stack web development | 1 |
Roles most likely to require econometrics
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Economist | 10 | 43.5% |
| Data Science Consultant | 11 | 16.2% |
| Senior Data Scientist | 3 | 11.1% |
| Quantitative Research Intern | 2 | 9.1% |
| Data Science Lead | 2 | 8.7% |
| Quantitative Finance Analyst | 2 | 8.3% |
| Decision Scientist | 3 | 7.1% |
| Data Analytics Specialist | 2 | 7.1% |
| Quantitative Analyst | 12 | 6.9% |
| Growth Analyst | 1 | 5.0% |
Roles with the most econometrics postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 63 | 26.1% |
| Quantitative Analyst | 12 | 5.0% |
| Data Science Consultant | 11 | 4.6% |
| Data Analyst | 10 | 4.1% |
| Economist | 10 | 4.1% |
| Quantitative Researcher | 8 | 3.3% |
| Analyst | 5 | 2.1% |
| Machine Learning Engineer | 4 | 1.7% |
| Analytics Director | 3 | 1.2% |
| Analytics Manager | 3 | 1.2% |
Top companies posting jobs requiring econometrics
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| SIA | 17 |
| WPP | 10 |
| Capital One | 8 |
| 8 | |
| Wayve | 6 |
| Anthropic | 6 |
| BlackRock | 6 |
| Truist | 5 |
| AstraZeneca | 5 |
| Uber | 4 |
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 econometrics
| Name | Postings | Share |
|---|---|---|
| San Francisco | 14 | 5.8% |
| New York City | 11 | 4.6% |
| London | 8 | 3.3% |
| McLean | 7 | 2.9% |
| Singapore | 7 | 2.9% |
| Amsterdam | 6 | 2.5% |
| Berlin | 6 | 2.5% |
| San Jose | 4 | 1.7% |
| Toronto | 4 | 1.7% |
Skills commonly paired with econometrics
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-29. 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 econometrics by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s econometrics postings by all econometrics 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 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (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
- 75a730fee4cfa6b6
- data_as_of
- 2026-10-29
- window_days
- 90