trade-off analysis jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, trade-off analysis appears in 235 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning trade-off analysis, with demand share up 44.3% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about trade-off analysis
+Is trade-off analysis in demand in 2026?
Yes. trade-off analysis appears in 235 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Product Manager accounts for the most postings mentioning trade-off analysis (26.4% of all postings mentioning trade-off analysis).
+What jobs require trade-off analysis?
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 trade-off analysis are Technical Product Lead (7.8% of that role’s postings mention trade-off analysis), Product Lead (7.5% of that role’s postings mention trade-off analysis), Group Product Manager (7.4% of that role’s postings mention trade-off analysis).
+What skills are commonly paired with trade-off analysis?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), trade-off analysis most often appears alongside security, Product Management, SQL, Python, design reviews.
+Where is trade-off analysis most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring trade-off analysis are Tel Aviv, London, Somerville, San Francisco, New York City, according to the Skillenai jobs index.
+How can I keep up with new trade-off analysis content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning trade-off analysis alongside the jobs index. You can subscribe to a daily email digest of new trade-off analysis content from your Skillenai account.
+Which skills come before and after trade-off analysis?
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 trade-off analysis — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around trade-off analysis
Skills documented before and after this skill across employer changes.
Not enough linked career history to draw this chart yet.
Roles most likely to require trade-off analysis
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Technical Product Lead | 22 | 7.8% |
| Product Lead | 12 | 7.5% |
| Group Product Manager | 10 | 7.4% |
| Finance Analyst | 2 | 6.2% |
| Embedded Software Architect | 1 | 4.2% |
| Product Operations Manager | 1 | 3.8% |
| IT Cybersecurity Specialist | 1 | 3.0% |
| Engineering Product Manager | 1 | 2.9% |
| Operations Program Manager | 2 | 2.5% |
| Solutions Architect | 43 | 1.8% |
Roles with the most trade-off analysis postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Product Manager | 62 | 26.4% |
| Solutions Architect | 43 | 18.3% |
| Technical Product Lead | 22 | 9.4% |
| Technical Product Manager | 14 | 6.0% |
| Product Lead | 12 | 5.1% |
| Program Manager | 11 | 4.7% |
| Group Product Manager | 10 | 4.3% |
| Systems Engineer | 10 | 4.3% |
| Technical Program Manager | 7 | 3.0% |
| Engineering Manager | 3 | 1.3% |
Top companies posting jobs requiring trade-off analysis
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Bjakcareer | 49 |
| Databricks | 41 |
| Unframe | 13 |
| Formlabs | 7 |
| Intuitive | 4 |
| Synthesia | 3 |
| Mimecast | 3 |
| Renesas | 2 |
| Bjak | 2 |
| Dbeaver.com | 2 |
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 trade-off analysis
| Name | Postings | Share |
|---|---|---|
| Tel Aviv | 12 | 5.1% |
| London | 7 | 3.0% |
| Somerville | 7 | 3.0% |
| San Francisco | 5 | 2.1% |
| New York City | 4 | 1.7% |
| Seoul | 4 | 1.7% |
| Sunnyvale | 4 | 1.7% |
| Sydney | 4 | 1.7% |
| Boston | 3 | 1.3% |
Skills commonly paired with trade-off analysis
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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 trade-off analysis by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s trade-off analysis postings by all trade-off analysis 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
- 9e92c73c3d60b1ac
- 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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