Skillenai

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

As of 2026-10-29, exploratory data analysis appears in 431 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning exploratory data analysis, with demand share up 12.3% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-29

Postings · last 90 days
431
Demand vs prior month
up 12.3% vs the prior 4 weeks
Top role · 43.2% 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 431 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Data Scientist accounts for the most postings mentioning exploratory data analysis (43.2% of all postings mentioning exploratory data analysis).

+What jobs require exploratory data analysis?

According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning exploratory data analysis are Data Scientist Intern (9.2% of that role’s postings mention exploratory data analysis), Data Analytics Consultant (9.1% of that role’s postings mention exploratory data analysis), Bioinformatics Scientist (8.3% 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 2026-10-29), exploratory data analysis most often appears alongside Python, SQL, machine learning, data visualization, R.

+Where is exploratory data analysis most in demand?

As of 2026-10-29, the metro areas posting the most jobs requiring exploratory data analysis are New York City, Bengaluru, London, San Francisco, Singapore, 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: 31 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 pairPower BI → exploratory data analysis: 10 observed employer moves with this skill pairR → exploratory data analysis: 10 observed employer moves with this skill pairpandas → exploratory data analysis: 9 observed employer moves with this skill pairExcel → exploratory data analysis: 8 observed employer moves with this skill pairETL → exploratory data analysis: 7 observed employer moves with this skill pairexploratorydata analysispython: 31 movespython31 movessql: 18 movessql18 movesTableau: 12 movesTableau12 movesPower BI: 10 movesPower BI10 movesR: 10 movesR10 movespandas: 9 movespandas9 movesExcel: 8 movesExcel8 movesETL: 7 movesETL7 moves

Skills after exploratory data analysis

After exploratory data analysisexploratory data analysis → Tableau: 20 observed employer moves with this skill pairexploratory data analysis → sql: 18 observed employer moves with this skill pairexploratory data analysis → Power BI: 17 observed employer moves with this skill pairexploratory data analysis → python: 16 observed employer moves with this skill pairexploratory data analysis → ETL: 8 observed employer moves with this skill pairexploratory data analysis → dashboards: 7 observed employer moves with this skill pairexploratory data analysis → Excel: 7 observed employer moves with this skill pairexploratory data analysis → spark: 6 observed employer moves with this skill pairexploratorydata analysisTableau: 20 movesTableau20 movessql: 18 movessql18 movesPower BI: 17 movesPower BI17 movespython: 16 movespython16 movesETL: 8 movesETL8 movesdashboards: 7 movesdashboards7 movesExcel: 7 movesExcel7 movesspark: 6 movesspark6 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: python31
Before: sql18
Before: Tableau12
Before: Power BI10
Before: R10
Before: pandas9
Before: Excel8
Before: ETL7
After: Tableau20
After: sql18
After: Power BI17
After: python16
After: ETL8
After: dashboards7
After: Excel7
After: spark6

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
Data Scientist Intern89.2%
Data Analytics Consultant39.1%
Bioinformatics Scientist28.3%
Technology Consultant38.1%
Deployment Engineer37.9%
Product Data Scientist37.1%
Analytics Intern27.1%
Data Analytics Intern35.8%
Data Science Intern35.6%
Data Analyst Intern35.1%

Roles with the most exploratory data analysis postings

RolePostings mentioning skillShare of skill postings
Data Scientist18643.2%
Data Analyst5212.1%
Machine Learning Engineer184.2%
ML Engineer153.5%
Data Engineer81.9%
Data Scientist Intern81.9%
Software Engineer71.6%
Applied Scientist51.2%
Business Intelligence Analyst40.9%
Scientific Data Architect40.9%

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
Amgen9
Bosch8
Uber6
Celonis6
Haus6
Torcrobotics5
PG5
Barclays5
Doximity5
City of New York4

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 City163.7%
Bengaluru143.2%
London102.3%
San Francisco102.3%
Singapore71.6%
Toronto71.6%
Amsterdam51.2%
Hyderabad51.2%
Thousand Oaks51.2%

Skills commonly paired with exploratory data analysis

Python (328)SQL (270)machine learning (220)data visualization (165)R (113)Tableau (103)feature engineering (96)Power BI (73)Statistical analysis (72)Statistical modeling (69)

Explore related pages

How this was computed

Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-29. 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: 0.2% 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 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (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
2026-10-29
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index