statistical models jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, statistical models appears in 155 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning statistical models, with demand share down 1.8% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
155
Demand vs prior month
down 1.8% vs the prior 4 weeks
Top role · 33.5% of skill postings
Top hiring metro
New York City

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Frequently asked questions about statistical models

+Is statistical models in demand in 2026?

Yes. statistical models appears in 155 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning statistical models (33.5% of all postings mentioning statistical models).

+What jobs require statistical models?

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 statistical models are Advanced Analytics Lead (17.4% of that role’s postings mention statistical models), Data Science Consultant (10.8% of that role’s postings mention statistical models), Bioinformatics Scientist (10.0% of that role’s postings mention statistical models).

+What skills are commonly paired with statistical models?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), statistical models most often appears alongside Python, machine learning, SQL, R, data visualization.

+Where is statistical models most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring statistical models are New York City, Mountain View, San Francisco, Singapore, Toronto, according to the Skillenai jobs index.

+How can I keep up with new statistical models content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning statistical models alongside the jobs index. You can subscribe to a daily email digest of new statistical models content from your Skillenai account.

+Which skills come before and after statistical models?

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 statistical models — last 90 days

Career paths around statistical models

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before statistical models

Before statistical modelspython → statistical models: 11 observed employer moves with this skill pairR → statistical models: 8 observed employer moves with this skill pairsql → statistical models: 7 observed employer moves with this skill pairPower BI → statistical models: 4 observed employer moves with this skill pairExcel → statistical models: 4 observed employer moves with this skill pairC++ → statistical models: 3 observed employer moves with this skill pairxgboost → statistical models: 3 observed employer moves with this skill pairTableau → statistical models: 3 observed employer moves with this skill pairstatisticalmodelspython: 11 movespython11 movesR: 8 movesR8 movessql: 7 movessql7 movesPower BI: 4 movesPower BI4 movesExcel: 4 movesExcel4 movesC++: 3 movesC++3 movesxgboost: 3 movesxgboost3 movesTableau: 3 movesTableau3 moves

Skills after statistical models

After statistical modelsstatistical models → python: 7 observed employer moves with this skill pairstatistical models → sql: 6 observed employer moves with this skill pairstatistical models → R: 3 observed employer moves with this skill pairstatistical models → dashboards: 3 observed employer moves with this skill pairstatistical models → Tableau: 3 observed employer moves with this skill pairstatistical models → statistical analysis: 3 observed employer moves with this skill pairstatistical models → Excel: 3 observed employer moves with this skill pairstatistical models → Git: 2 observed employer moves with this skill pairstatisticalmodelspython: 7 movespython7 movessql: 6 movessql6 movesR: 3 movesR3 movesdashboards: 3 movesdashboards3 movesTableau: 3 movesTableau3 movesstatistical analysis: 3 movesstatisticalanalysis3 movesExcel: 3 movesExcel3 movesGit: 2 movesGit2 moves
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.

Observed connections and move counts
ConnectionMoves
Before: python11
Before: R8
Before: sql7
Before: Power BI4
Before: Excel4
Before: C++3
Before: xgboost3
Before: Tableau3
After: python7
After: sql6
After: R3
After: dashboards3
After: Tableau3
After: statistical analysis3
After: Excel3
After: Git2

Roles most likely to require statistical models

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Advanced Analytics Lead417.4%
Data Science Consultant810.8%
Bioinformatics Scientist210.0%
Credit Risk Manager29.1%
Data Science Director35.1%
AI/ML Scientist14.3%
Data Consultant14.2%
Analytics Specialist13.8%
Finance Data Analyst13.7%
Analytics Intern13.6%

Roles with the most statistical models postings

RolePostings mentioning skillShare of skill postings
Data Scientist5233.5%
Machine Learning Engineer117.1%
Data Science Consultant85.2%
Data Analyst63.9%
Software Engineer53.2%
Advanced Analytics Lead42.6%
Applied Scientist31.9%
Data Science Director31.9%
Analytics Lead21.3%
Associate Scientist21.3%

Top companies posting jobs requiring statistical models

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring statistical models
CompanyPostings · 90 days
Accenture11
JPMorgan Chase & Co.5
Airbnb4
Waymo4
Barclays3
NBCUniversal3
JJ3
HotelTonight2
Blue Cross2
Uber Freight2

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 statistical models

NamePostingsShare
New York City127.7%
Mountain View63.9%
San Francisco53.2%
Singapore53.2%
Toronto53.2%
Washington53.2%
Chicago42.6%
Boston31.9%
Columbus31.9%

Skills commonly paired with statistical models

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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 statistical models by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s statistical models postings by all statistical models 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
29dee63509aa6229
data_as_of
2026-09-30
window_days
90
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Compiled by Jared Rand · Data sourced from the Skillenai labor market index