demand forecasting jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, demand forecasting appears in 219 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning demand forecasting, with demand share up 12.6% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about demand forecasting
+Is demand forecasting in demand in 2026?
Yes. demand forecasting appears in 219 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Product Manager accounts for the most postings mentioning demand forecasting (12.3% of all postings mentioning demand forecasting).
+What jobs require demand forecasting?
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 demand forecasting are Business Operations Manager (11.8% of that role’s postings mention demand forecasting), Enterprise Solution Architect (9.1% of that role’s postings mention demand forecasting), Machine Learning Manager (8.0% of that role’s postings mention demand forecasting).
+What skills are commonly paired with demand forecasting?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), demand forecasting most often appears alongside Python, SQL, machine learning, forecasting, capacity planning.
+Where is demand forecasting most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring demand forecasting are London, San Francisco, New York City, Berlin, Manchester, according to the Skillenai jobs index.
+How can I keep up with new demand forecasting content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning demand forecasting alongside the jobs index. You can subscribe to a daily email digest of new demand forecasting content from your Skillenai account.
+Which skills come before and after demand forecasting?
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 demand forecasting — last 90 days
Career paths around demand forecasting
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before demand forecasting
Skills after demand forecasting
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 | 7 |
| Before: sql | 5 |
| Before: pandas | 3 |
| Before: Tableau | 3 |
| Before: scikit-learn | 2 |
| Before: data modeling | 2 |
| Before: numpy | 2 |
| Before: T-SQL | 2 |
| After: Power BI | 5 |
| After: python | 4 |
| After: sql | 4 |
| After: Transformers | 3 |
| After: PySpark | 3 |
| After: BERT | 3 |
| After: logistic regression | 3 |
| After: Tableau | 3 |
Roles most likely to require demand forecasting
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Business Operations Manager | 4 | 11.8% |
| Enterprise Solution Architect | 2 | 9.1% |
| Machine Learning Manager | 2 | 8.0% |
| Applied Scientist | 11 | 4.4% |
| AI Analyst | 1 | 3.4% |
| Data Engineer Intern | 1 | 3.2% |
| Business Intelligence Manager | 3 | 3.2% |
| Sales Director | 1 | 2.9% |
| Senior Data Engineer | 1 | 2.8% |
| Applied Value Engineer | 1 | 2.5% |
Roles with the most demand forecasting postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Product Manager | 27 | 12.3% |
| Data Scientist | 20 | 9.1% |
| Applied Scientist | 11 | 5.0% |
| Technical Program Manager | 10 | 4.6% |
| Business Analyst | 8 | 3.7% |
| Data Analyst | 5 | 2.3% |
| Forward Deployed Scientist | 5 | 2.3% |
| Program Manager | 5 | 2.3% |
| Site Reliability Engineer | 5 | 2.3% |
| Strategy & Analytics Manager | 5 | 2.3% |
Top companies posting jobs requiring demand forecasting
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| SpaceX | 7 |
| UiPath | 6 |
| Monzo | 5 |
| Quince | 4 |
| Amazon | 4 |
| GoPuff | 4 |
| General Motors | 4 |
| Xometry | 4 |
| Relay | 4 |
| Coupanginternal | 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 demand forecasting
| Name | Postings | Share |
|---|---|---|
| London | 9 | 4.1% |
| San Francisco | 9 | 4.1% |
| New York City | 8 | 3.7% |
| Berlin | 6 | 2.7% |
| Manchester | 5 | 2.3% |
| Mountain View | 5 | 2.3% |
| Bengaluru | 4 | 1.8% |
| San Jose | 4 | 1.8% |
| Taipei | 4 | 1.8% |
Skills commonly paired with demand forecasting
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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 demand forecasting by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s demand forecasting postings by all demand forecasting 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
- 8262976f7a8288ac
- 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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