data-driven insights jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, data-driven insights appears in 317 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning data-driven insights, with demand share up 4.4% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about data-driven insights
+Is data-driven insights in demand in 2026?
Yes. data-driven insights appears in 317 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Product Manager accounts for the most postings mentioning data-driven insights (25.6% of all postings mentioning data-driven insights).
+What jobs require data-driven insights?
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-driven insights are Advanced Analytics Lead (13.0% of that role’s postings mention data-driven insights), Business Operations Manager (5.9% of that role’s postings mention data-driven insights), Commercial Analytics Manager (4.5% of that role’s postings mention data-driven insights).
+What skills are commonly paired with data-driven insights?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), data-driven insights most often appears alongside Data analysis, SQL, automation, Product Management, product strategy.
+Where is data-driven insights most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring data-driven insights are New York City, San Francisco, Toronto, San Antonio, Madrid, according to the Skillenai jobs index.
+How can I keep up with new data-driven insights content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning data-driven insights alongside the jobs index. You can subscribe to a daily email digest of new data-driven insights content from your Skillenai account.
+Which skills come before and after data-driven insights?
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-driven insights — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around data-driven insights
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before data-driven insights
Skills after data-driven insights
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: python | 5 |
| Before: sql | 4 |
| Before: AWS | 3 |
| Before: ETL | 2 |
| Before: interactive dashboards | 2 |
| Before: Power BI | 2 |
| Before: actionable insights | 2 |
| Before: Git | 2 |
| After: data analysis | 7 |
| After: dashboards | 4 |
| After: python | 3 |
| After: design system | 3 |
| After: a/b testing | 3 |
| After: visualizations | 3 |
| After: prompt engineering | 2 |
| After: predictive models | 2 |
Roles most likely to require data-driven insights
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Advanced Analytics Lead | 3 | 13.0% |
| Business Operations Manager | 2 | 5.9% |
| Commercial Analytics Manager | 1 | 4.5% |
| Credit Risk Manager | 1 | 4.5% |
| Analytics Leader | 1 | 3.7% |
| Marketing Analytics Director | 1 | 3.7% |
| Sales Operations Manager | 1 | 3.6% |
| Data Science Director | 2 | 3.4% |
| Marketing Analytics Manager | 2 | 3.1% |
| Marketing Analyst | 2 | 3.1% |
Roles with the most data-driven insights postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Product Manager | 81 | 25.6% |
| Program Manager | 19 | 6.0% |
| Data Analyst | 14 | 4.4% |
| Engineering Manager | 10 | 3.2% |
| Business Analyst | 8 | 2.5% |
| Product Owner | 6 | 1.9% |
| AI Search Innovation Lead | 4 | 1.3% |
| Data Scientist | 4 | 1.3% |
| Digital/Technical Product Manager | 4 | 1.3% |
| AI Product Manager | 3 | 0.9% |
Top companies posting jobs requiring data-driven insights
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| USAA | 15 |
| Feverup | 8 |
| Cisco | 7 |
| WPP | 6 |
| Amazon | 5 |
| Barclays | 5 |
| Snowflake | 5 |
| Adyen | 4 |
| Twilio | 4 |
| Databricks | 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 data-driven insights
| Name | Postings | Share |
|---|---|---|
| New York City | 19 | 6.0% |
| San Francisco | 10 | 3.2% |
| Toronto | 10 | 3.2% |
| San Antonio | 7 | 2.2% |
| Madrid | 6 | 1.9% |
| Arlington | 5 | 1.6% |
| Barcelona | 5 | 1.6% |
| Bengaluru | 5 | 1.6% |
| Hong Kong | 5 | 1.6% |
Skills commonly paired with data-driven insights
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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 data-driven insights by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data-driven insights postings by all data-driven insights 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
- ec4758f6bd6bc1fe
- data_as_of
- 2026-09-30
- window_days
- 90
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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