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exploratory data analysis jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, exploratory data analysis appears in 360 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning exploratory data analysis, with demand share up 3.2% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
360
Demand vs prior month
up 3.2% vs the prior 4 weeks
Top role · 45.0% of skill postings
Data Scientist
Top hiring metro
New York City

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Frequently asked questions about exploratory data analysis

+Is exploratory data analysis in demand in 2026?

Yes. exploratory data analysis appears in 360 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning exploratory data analysis (45.0% of all postings mentioning exploratory data analysis).

+What jobs require exploratory data 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 exploratory data analysis are Bioinformatics Scientist (10.0% of that role’s postings mention exploratory data analysis), Product Data Scientist (9.5% of that role’s postings mention exploratory data analysis), Data Scientist Intern (9.2% of that role’s postings mention exploratory data analysis).

+What skills are commonly paired with exploratory data analysis?

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

+Where is exploratory data analysis most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring exploratory data analysis are New York City, London, Bengaluru, San Francisco, Toronto, according to the Skillenai jobs index.

+How can I keep up with new exploratory data analysis content and jobs?

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

+Which skills come before and after exploratory data 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 exploratory data analysis — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around exploratory data analysis

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before exploratory data analysis

Before exploratory data analysispython → exploratory data analysis: 27 observed employer moves with this skill pairsql → exploratory data analysis: 18 observed employer moves with this skill pairTableau → exploratory data analysis: 12 observed employer moves with this skill pairR → exploratory data analysis: 10 observed employer moves with this skill pairPower BI → exploratory data analysis: 9 observed employer moves with this skill pairExcel → exploratory data analysis: 8 observed employer moves with this skill pairpandas → exploratory data analysis: 8 observed employer moves with this skill pairscikit-learn → exploratory data analysis: 6 observed employer moves with this skill pairexploratorydata analysispython: 27 movespython27 movessql: 18 movessql18 movesTableau: 12 movesTableau12 movesR: 10 movesR10 movesPower BI: 9 movesPower BI9 movesExcel: 8 movesExcel8 movespandas: 8 movespandas8 movesscikit-learn: 6 movesscikit-learn6 moves

Skills after exploratory data analysis

After exploratory data analysisexploratory data analysis → Tableau: 19 observed employer moves with this skill pairexploratory data analysis → sql: 17 observed employer moves with this skill pairexploratory data analysis → Power BI: 17 observed employer moves with this skill pairexploratory data analysis → python: 14 observed employer moves with this skill pairexploratory data analysis → ETL: 7 observed employer moves with this skill pairexploratory data analysis → dashboards: 7 observed employer moves with this skill pairexploratory data analysis → data cleaning: 6 observed employer moves with this skill pairexploratory data analysis → snowflake: 6 observed employer moves with this skill pairexploratorydata analysisTableau: 19 movesTableau19 movessql: 17 movessql17 movesPower BI: 17 movesPower BI17 movespython: 14 movespython14 movesETL: 7 movesETL7 movesdashboards: 7 movesdashboards7 movesdata cleaning: 6 movesdata cleaning6 movessnowflake: 6 movessnowflake6 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: python27
Before: sql18
Before: Tableau12
Before: R10
Before: Power BI9
Before: Excel8
Before: pandas8
Before: scikit-learn6
After: Tableau19
After: sql17
After: Power BI17
After: python14
After: ETL7
After: dashboards7
After: data cleaning6
After: snowflake6

Roles most likely to require exploratory data analysis

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

RolePostings mentioning skill% of role postings mentioning skill
Bioinformatics Scientist210.0%
Product Data Scientist69.5%
Data Scientist Intern89.2%
Data Analytics Consultant38.3%
People Analytics Analyst27.4%
Technology Consultant26.9%
Deployment Engineer25.0%
Data Science Engineer24.8%
Data Science Intern24.5%
Data Analyst Intern34.3%

Roles with the most exploratory data analysis postings

RolePostings mentioning skillShare of skill postings
Data Scientist16245.0%
Data Analyst3910.8%
Machine Learning Engineer133.6%
ML Engineer123.3%
Data Scientist Intern82.2%
Data Engineer61.7%
Product Data Scientist61.7%
Applied Scientist51.4%
Machine Learning Scientist51.4%
Scientific Data Architect41.1%

Top companies posting jobs requiring exploratory data analysis

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

Top companies posting jobs requiring exploratory data analysis
CompanyPostings · 90 days
Haus6
Tripadvisor6
Bosch6
PG5
Barclays5
Artefact5
Uber4
Celonis4
Treasure AI4
Roku4

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 exploratory data analysis

NamePostingsShare
New York City154.2%
London143.9%
Bengaluru102.8%
San Francisco92.5%
Toronto61.7%
Chicago51.4%
Cincinnati51.4%
San Jose51.4%
Montréal41.1%

Skills commonly paired with exploratory data analysis

Python (270)SQL (205)machine learning (176)data visualization (155)R (95)Tableau (89)feature engineering (73)Statistical analysis (62)Statistical modeling (61)Power BI (57)

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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 exploratory data analysis by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s exploratory data analysis postings by all exploratory data 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 0.2%. 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
4a5d6b7c93a367f9
data_as_of
2026-09-30
window_days
90
Hiring engineers who use exploratory data analysis?

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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Compiled by Jared Rand · Data sourced from the Skillenai labor market index