Is Data, Analytics & AI a Good Job Market in Philadelphia-Camden-Wilmington, PA-NJ-DE-MD?

Executive Verdict

Market rating: competitive | Confidence: High

Philadelphia is a good but selective market for Data, Analytics & AI over the next 3-6 months. Metro unemployment was 4.1% in May 2026, while Pennsylvania Data, Analytics & AI postings were up 22.6% year over year even as statewide employment in the field was essentially flat, which usually means openings exist but employers are still choosy.[6][7][8] In the recent local sample, there were more than 175 postings across more than 100 companies, with healthcare, technology, and financial services leading the mix.[9][10] Pay is attractive, but access is uneven: only about 10% of sampled postings were entry-level and only about 10% were remote.[11][12]

Best positioned: Candidates with Python and SQL, plus either machine learning or strong reporting/visualization depth, and willingness to work hybrid or on-site have the best odds because Python appears in about 70% of sampled postings, SQL in about 45%, and remote roles make up only about 10% of the mix.[1][12]

Main caution: Do not mistake high salary headlines for easy access; local ranges are wide, and a recent Philadelphia academic-medicine data analyst role paid roughly $62,067-$80,000 even while the broader local posting sample centered on about $109k to $170k.[3][13]

What Changed Recently

• The strongest recent demand signal is at the state occupation level: Data, Analytics & AI postings in Pennsylvania were up 22.6% year over year in June 2026, while employment in the field was essentially flat.[7][8]: That usually means more openings are appearing, but not enough broad hiring to make this an easy market; expect active requisitions with tighter screening.[7][8]
• The broader Philadelphia labor market improved into May 2026: metro unemployment was 4.1%, the unemployment level was down -3.4556% year over year, employment was up 2.0725%, and the labor force was up 1.8350%.[6][19][20][21]: That is a better backdrop for job search than a weakening metro economy, especially for roles tied to enterprise analytics budgets.[6][20][21]
• Local opportunity is spread across a long employer list rather than one dominant buyer, with more than 175 postings across more than 100 companies over the last 90 days and a fragmented employer mix.[9][29]: You should run a broad, targeted search across healthcare, consulting, finance, and academic employers instead of waiting for one marquee company to open the right role.[9][10]
• Nationally, JOLTS job openings reached 7,594 thousand in May 2026 and were up 3.8851% year over year, but hires were down -2.9655% and quits were down -6.7539%.[15][16][17]: For Philadelphia candidates, that points to a market with posted opportunities but slower hiring motion, so interview cycles may feel longer and conversion from application to offer may be tougher than the openings count suggests.[15][16][17]

What This Means for You

Entry-Level Candidates

Difficulty: High.

Best target: On-site or hybrid analyst roles in healthcare systems, university research groups, enterprise reporting teams, and consulting support functions.

Biggest mistake: Applying mostly to remote data scientist or AI-heavy titles without proof that you can ship useful SQL, Python, and dashboard work.

Next step: Build one portfolio piece that answers a business question end to end: clean data in SQL, analyze in Python, and present results in a dashboard or memo.

Mid-Career Candidates

Difficulty: Moderate to high, but much better than entry level.

Best target: Enterprise roles in healthcare, financial services, and consulting where you can show measurable business impact, not just technical fluency.

Biggest mistake: Presenting as a generic 'data professional' instead of showing a clear wedge such as experimentation, forecasting, risk analytics, operational analytics, or applied ML.

Next step: Split your resume into two versions: one for analyst/BI roles and one for advanced analytics or AI roles, each with domain-specific outcomes and tool choices.

Career Switchers

Difficulty: High unless you can bring strong domain context.

Best target: BI, reporting, operations analytics, or decision-support roles close to your current industry rather than jumping straight to pure data science titles.

Biggest mistake: Leading with a bootcamp or certification alone and not translating your prior work into KPIs, process improvement, forecasting, or stakeholder influence.

Next step: Use your old domain as the hook, then add one proof project that mirrors a real employer problem in healthcare, finance, or consulting.

Salary Reality

high pay highly concentrated

Observed local posted salary ranges for the category center on about $109k to $170k, with a broader 25th-75th band of about $93k to $195k.[13] As directional benchmarks, Pennsylvania's mean offered salary on new Data, Analytics & AI openings was ~$107,298 (n=1,508) and the national mean offered salary was ~$124,005 (n=150,794).[23] Local examples still vary sharply by employer type, including a Philadelphia academic-medicine data analyst role at roughly $62,067-$80,000.[3]

Philadelphia looks like a high-paying analytics market relative to many metros. Robert Half says local data analyst pay runs about 16.5% above the national midpoint here, which is consistent with the stronger local posting ranges.[5][13]

The salary upside comes with selectivity. Only about 10% of sampled postings were entry-level, and only about 10% were remote, so many of the better-paying roles are also the ones with tougher experience and location filters.[11][12]

Best-paying path: The strongest pay signals sit in analytics engineering, advanced enterprise analytics, and AI-heavy work. A lagged metro estimate put analytics engineer pay at $157,200 mean and $163,590 median, while the broader local posting sample suggests many non-entry roles still cluster lower than that.[31][13]

Caution: Do not overread the top end. These numbers mix different sub-roles and employer types, and local analyst compensation can drop materially in academia or mission-driven healthcare settings even when the metro-wide picture looks strong.[3][13]

Where the Opportunities Are Concentrated

Real opportunity is concentrated by buyer type, not evenly distributed across every employer. In the recent local sample, healthcare accounted for about 25% of postings, technology about 20%, financial services about 15%, with finance & accounting and information technology each around 10%.[10] About 45% of postings came from enterprise employers, and hiring was fragmented rather than dominated by a single company.[30][29] That matters because different submarkets want different versions of 'data' talent. Healthcare and academic medicine are signaling demand for analysts who can handle machine learning, AI, signal processing, quantitative modeling, and multimodal data workflows, as shown by the Perelman School of Medicine role in Philadelphia.[3] Financial services and consulting employers such as Vanguard Group, Deloitte, CACI, and Kpmg Us also appear repeatedly in the local sample, which favors candidates who can connect Python and SQL work to decision support, reporting, risk, or operational improvement.[24][1] Because only about 10% of sampled postings were entry-level and most roles are on-site or hybrid, the best near-term opportunities are with enterprise employers in healthcare, financial services, and consulting that need applied analytics rather than purely research-oriented AI.[11][12][30]

• Healthcare and academic medicine (high): This is the single largest local demand pocket at about 25% of postings, and recent Philadelphia hiring signals ask for machine learning, AI, signal processing, and quantitative modeling in applied research settings.[10][3]
• Financial services and consulting (high): Financial services represent about 15% of the sample, and recurring named employers include Vanguard Group, Deloitte, CACI, and Kpmg Us, which points to steady need for business-facing analytics and decision support.[10][24]
• Generalist tech and information roles (moderate): Technology and IT together account for roughly 30% of the sample, but these roles are still more promising when they emphasize analytics, modeling, and BI work rather than software-platform ownership.[10]

Where to focus: Focus first on hybrid or on-site Python + SQL roles in healthcare, financial services, and consulting, then stretch into ML-heavy titles once you can show domain-specific work samples.[10][1][12]

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 70% of sampled local postings, making it the clearest screen-in skill across analyst, scientist, and AI-oriented roles.[1]
• SQL (table stakes): SQL shows up in about 45% of local postings, and outside reports also highlight advanced SQL as a high-impact skill for analysts.[1][2]
• Machine learning and applied AI (premium): Machine learning appears in about 25% of local postings, and a recent Philadelphia academic-healthcare role explicitly preferred machine learning and AI experience.[1][3]
• Data visualization (differentiator): Data visualization appears in about 20% of local postings, which makes it a practical differentiator for turning technical analysis into business decisions.[1]
• R and statistical analysis (differentiator): R appears in about 20% of the local sample and statistical analysis in about 15%, which is especially useful in healthcare, research, and more quantitative analyst tracks.[1]
• AWS and cloud analytics tools (differentiator): AWS appears in about 15% of local postings, and the most commonly required certification in the local sample is AWS Solutions Architect at about 5%.[1][4]
• Analytics/BI or data science certification (premium): Robert Half says relevant certifications can lift compensation for U.S. data analyst and BI roles by about 10% to 20%, with analytics and BI credentials averaging a 16.6% bump, and data science or big data certifications averaging a 17.9% premium.[2][5]

Adjacent Roles to Consider

• Business analyst (bridge): Many local openings sit in enterprise healthcare, finance, and consulting environments where SQL, reporting, and stakeholder translation matter even when the title is not pure analytics.[30][10][1]
• Operations analyst (bridge): The local mix favors applied decision support in large employers, which makes KPI tracking, forecasting, and dashboard work transferable into operations-focused roles.[30][10][1]
• FP&A or financial analyst (pivot): Financial services account for about 15% of the local sample, making finance-facing analysis a credible side-step for candidates who can move from data wrangling into forecasting and variance analysis.[10]
• Risk or compliance analyst (both): Regulated healthcare and finance employers value statistical analysis, SQL, and audit-friendly reporting, which overlap with this market's common requirements.[10][1]

30 / 60 / 90-Day Plan

First 30 Days

• Rewrite your resume into two tracks: analyst/BI and advanced analytics/AI, with different project bullets and keywords for each.
• Build one portfolio case in healthcare or finance that starts with messy data, uses SQL and Python, and ends with a dashboard plus a one-page decision memo.
• Stop mass-applying to remote-only roles and build a target list for hybrid and on-site employers across healthcare, consulting, finance, and universities.
• Create a reusable interview pack: 12 SQL queries, 3 Python notebooks, 2 business case stories, and 1 clear explanation of a model you built.

Days 31-60

• Add one missing differentiator only if it matches your target roles: data visualization depth, AWS/cloud analytics fluency, or stronger statistical testing.
• Publish a second project that shows domain judgment, such as patient-flow analytics, churn or retention analysis, fraud/risk monitoring, or operational forecasting.
• Practice timed SQL screens and business-translation interviews, not just technical coding exercises.
• Ask every contact and recruiter which of your backgrounds they see as strongest: healthcare, finance, operations, or research, then narrow your search around that wedge.

Days 61-90

• If response rates stay weak, step sideways into business analyst, operations analyst, FP&A, or risk/compliance analyst roles that still reward your analytics stack.
• Adjust title targeting downward before you adjust pay expectations upward; in this market, a narrower title match usually matters more than a broad senior label.
• If you need sponsorship or fully remote work, widen your search beyond Philadelphia rather than waiting for the local mix to bend in your favor.
• Use your interview feedback to choose one durable specialty for the next quarter: experimentation, forecasting, healthcare research analytics, or business intelligence.

Methodology and Confidence

This June 2026 report was generated on July 10, 2026. Latest direct national data: June 2026. Latest direct Philadelphia-Camden-Wilmington, PA-NJ-DE-MD data: July 2026.

Confidence: Overall confidence: High. The report is anchored in recent local labor data and supported by multiple current local and state signals.

Limitations

• The freshest direct Philadelphia-area labor-market readings used here are from May 2026, so any sharp turn after that month may not yet appear in the core local numbers.[6][19][20][21]
• Several government year-over-year local changes for May 2026 are preliminary and may be revised later, so treat small changes as directional rather than final.[6][19][20][21][22]
• Statewide occupation data from Revelio Public Labor Statistics was used as a proxy for metro-level direction because a comparable metro occupation series is not published here, and conditions can differ across the Philadelphia, Camden, and Wilmington parts of the region.[8][7][23]
• This category combines data analyst, data scientist, BI, analytics engineering, and AI-oriented work, so pay and competition can vary a lot by sub-role; local examples range from roughly $62,067-$80,000 in academic medicine to broader posted ranges centered on about $109k to $170k.[3][13]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so direction of demand, leading employer names, and skill patterns are more reliable than exact counts or shares.[9][24][10][1]

References

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2. Robert Half. 2026 Data Analyst Salary Trends: What You Need to Know · 2025-09 · roberthalf.com
3. Higheredjobs. Higheredjobs - top_employer · 2026-06 · higheredjobs.com
4. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
5. Robert Half. 2026 Technology salary trends: The skills and roles driving growth · 2025-09 · roberthalf.com
6. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
7. Reveliolabs. Job Openings - Revelio Public Labor Statistics (RPLS) · 2026-06 · reveliolabs.com
8. Reveliolabs. Employment - Revelio Public Labor Statistics (RPLS) · 2026-06 · reveliolabs.com
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14. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
15. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
16. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
17. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
18. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.bls.gov
19. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
20. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
21. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
22. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-05 · data.bls.gov
23. Reveliolabs. Salaries - Revelio Public Labor Statistics (RPLS) · 2026-06 · reveliolabs.com
24. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
25. Nj. Nj - warn_notice_layoff · 2026-06 · nj.gov
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28. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
29. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
30. Callings.ai. Callings.ai job-market aggregation · 2026-06 · callings.ai
31. Jobcannon. JobCannon: 121+ Free Personality & Career Tests + Career Match · 2025-01 · jobcannon.io