Collaborative filtering jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, Collaborative filtering appears in 36 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning Collaborative filtering.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about Collaborative filtering
+Is Collaborative filtering in demand in 2026?
Yes. Collaborative filtering appears in 36 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning Collaborative filtering (22.2% of all postings mentioning Collaborative filtering).
+What jobs require Collaborative filtering?
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 Collaborative filtering are Founding AI Engineer (14.3% of that role’s postings mention Collaborative filtering), Applied Researcher (2.4% of that role’s postings mention Collaborative filtering), Data Science Director (1.7% of that role’s postings mention Collaborative filtering).
+What skills are commonly paired with Collaborative filtering?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), Collaborative filtering most often appears alongside Python, embeddings, machine learning, SQL, A/B testing.
+Where is Collaborative filtering most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring Collaborative filtering are San Francisco, Annapolis, Bengaluru, Bucharest, Chicago, according to the Skillenai jobs index.
+How can I keep up with new Collaborative filtering content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Collaborative filtering alongside the jobs index. You can subscribe to a daily email digest of new Collaborative filtering content from your Skillenai account.
+Which skills come before and after Collaborative filtering?
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 Collaborative filtering — last 90 days
Career paths around Collaborative filtering
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Collaborative filtering
Skills after Collaborative filtering
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 | 10 |
| Before: Power BI | 8 |
| Before: sql | 7 |
| Before: Random Forest | 5 |
| Before: Tableau | 5 |
| Before: Apache Spark | 4 |
| Before: feature engineering | 4 |
| Before: data quality checks | 3 |
| After: pytorch | 7 |
| After: python | 5 |
| After: LLMs | 4 |
| After: sql | 4 |
| After: ARIMA | 4 |
| After: kubernetes | 4 |
| After: xgboost | 4 |
| After: SHAP | 3 |
Roles most likely to require Collaborative filtering
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Founding AI Engineer | 3 | 14.3% |
| Applied Researcher | 1 | 2.4% |
| Data Science Director | 1 | 1.7% |
| Applied Scientist | 4 | 1.6% |
| AI Scientist | 1 | 1.1% |
| AI Software Engineer | 3 | 1.1% |
| Lead Data Scientist | 1 | 1.0% |
| Data Scientist | 8 | 0.1% |
| AI Engineer | 4 | 0.1% |
| ML Engineer | 1 | 0.1% |
Roles with the most Collaborative filtering postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 8 | 22.2% |
| AI Engineer | 4 | 11.1% |
| Applied Scientist | 4 | 11.1% |
| AI Software Engineer | 3 | 8.3% |
| Director, Data Science | 3 | 8.3% |
| Founding AI Engineer | 3 | 8.3% |
| Product Manager | 2 | 5.6% |
| AI Scientist | 1 | 2.8% |
| AI/ML Executive Director | 1 | 2.8% |
| Applied Researcher | 1 | 2.8% |
Top companies posting jobs requiring Collaborative filtering
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| CLERA | 6 |
| GoPuff | 4 |
| Launch Potato | 4 |
| Mastercard | 2 |
| Goatgroup | 1 |
| Oura | 1 |
| eBay | 1 |
| MeantToBe | 1 |
| Rula | 1 |
| Airkit | 1 |
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 Collaborative filtering
| Name | Postings | Share |
|---|---|---|
| San Francisco | 7 | 19.4% |
| Annapolis | 2 | 5.6% |
| Bengaluru | 1 | 2.8% |
| Bucharest | 1 | 2.8% |
| Chicago | 1 | 2.8% |
| Fort Meade | 1 | 2.8% |
| Kuala Lumpur | 1 | 2.8% |
| Los Angeles | 1 | 2.8% |
| Mountain View | 1 | 2.8% |
Skills commonly paired with Collaborative filtering
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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 Collaborative filtering by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Collaborative filtering postings by all Collaborative filtering 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). An adjusted trend is not shown because comparable posting coverage is insufficient.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- d3f27f2099f20db7
- 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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