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

Executive Verdict

Market rating: competitive | Confidence: Medium

Philadelphia is a competitive but still worthwhile market for Data, Analytics & AI over the next 3-6 months. The metro labor market is healthier than a year ago, with unemployment at 4.1% in June 2026, metro employment up 2.0513% year-over-year, and the labor force up 1.4046% year-over-year.[12][13][14] For this occupation family, Pennsylvania-level signals are better than the all-jobs backdrop: Revelio Public Labor Statistics shows Data, Analytics & AI postings up 18.4% year-over-year while statewide employment in the field is essentially flat, which usually means openings exist but employers are being selective.[11][10] Locally, we observed more than 125 postings across more than 75 companies over the last 90 days, but only about 15% were entry-level and only about 10% were remote.[15][1][23]

Best positioned: Mid-career candidates who can show Python, SQL, machine learning, and business-facing delivery, especially in healthcare, financial services, or enterprise governance work, have the best odds right now.[4][3][8]

Main caution: The main risk is assuming that visible analytics hiring means easy hiring: this market skews toward mid and senior talent, enterprise employers, and hybrid or on-site work.[1][29][23]

What Changed Recently

• The Philadelphia metro labor market tightened versus a year earlier: unemployment was 4.1% in June 2026, down -12.7660% year-over-year, while total employment rose 2.0513% and the labor force rose 1.4046%.[12][13][14]: That is a better backdrop than a cooling market, but it does not automatically make white-collar analytics hiring easy.
• For Data, Analytics & AI specifically, Pennsylvania postings were up 18.4% year-over-year in July 2026 even as employment in the field was essentially flat, according to Revelio Public Labor Statistics.[11][10]: That combination usually means more open searches without broad-based headcount expansion, so employers are likely to be choosier and slower.
• Comcast posted multiple Philadelphia-tied analytics roles in late July and early August, including a Business Intelligence Analyst 2 role, a Data Solutions Fin Ops Principal role, and a Snowflake Data Governance Steward opening.[8]: This is a concrete local signal that BI, governance, and analytics leadership work is still being hired for in the metro.
• Nationally, total nonfarm employment reached 158,858 thousand in July 2026, up 0.1993% year-over-year, and the JOLTS openings rate was 4.4% in June 2026.[19][32]: The broader U.S. market is still adding jobs and holding openings, but not in a way that supports casual applications or fast interview cycles for analytics candidates.

What This Means for You

Entry-Level Candidates

Difficulty: Harder than average locally because only about 15% of sampled postings were entry-level, and bachelor's degrees were the dominant stated baseline where education was listed.[1][2]

Best target: Business-facing analyst work in healthcare, insurance, and enterprise reporting where Python, SQL, and dashboard skills beat pure model-building ambitions.[3][4][5]

Biggest mistake: Leading with certificates alone when local postings more often reward skills and project depth than explicit certification requirements; AWS certifications appeared in less than 5% of sampled postings.[6]

Next step: Build one portfolio pack with a healthcare operations dashboard, a finance or risk SQL case, and a short memo that turns analysis into a recommendation.

Mid-Career Candidates

Difficulty: Moderate: the market is competitive, but most openings cluster at mid and senior levels and the employer base is fragmented rather than dominated by one firm.[1][7]

Best target: Roles with ownership of BI, data modeling, governance, or decision support inside healthcare, financial services, consulting, and tech.[3][5][8]

Biggest mistake: Applying as a generic data person instead of packaging yourself around one business domain and one delivery stack.

Next step: Retool your resume into two versions, one for BI and governance work and one for advanced analytics, and make every bullet prove business impact.

Career Switchers

Difficulty: Hard unless you already have domain depth, because the market rewards business partnering and specialized context more than beginner technical breadth.[5][3]

Best target: Domain-adjacent analyst paths such as operations, healthcare, or insurance analytics where prior industry knowledge can substitute for years of formal analytics title history.[3]

Biggest mistake: Targeting AI engineer titles first when the local evidence is much stronger for analyst, BI, governance, and decision-support work.[8][4]

Next step: Pick one industry lane, get Python and SQL to interview level, and publish a portfolio that mirrors the metrics and reporting decisions used in that industry.

Salary Reality

high pay highly concentrated

The cleanest observed local pay point is BLS wage data for data scientists: median annual pay was $112,590 in the Philadelphia metro, with the 25th percentile at $90,520 and the 75th percentile at $144,790 in May 2024.[9] More current posting-based signals for the broader category center on about $116k to $175k locally, while statewide new openings averaged about $106,439 in offered salary in July 2026 on a sample of 1,509 postings from Revelio Public Labor Statistics.[17][33]

This is a good-paying market, but not an ultra-premium one. Local technology salaries average 94% of the national benchmark, and a useful national floor for entry-level data analyst pay is about $55,000 to $72,000, so Philadelphia tends to pay better than true entry-level norms while still trailing the very top U.S. markets.[34][35]

The upside is offset by access and specialization: only about 15% of sampled roles were entry-level, about 40% came from enterprise employers, and only about 10% were remote.[1][29][23]

Best-paying path: The strongest pay tends to sit in data science, analytics engineering, and AI or ML-leaning roles. National benchmarks put data scientist pay at $121,750 / $153,750 / $182,500 low-mid-high, while analytics engineers show a median employer-published salary around $175,000 across major U.S. metros.[36][18]

Caution: Do not overread the top of local salary bands: they blend multiple titles, experience levels, and employers, and they likely overrepresent senior, enterprise, or scarce-skill openings rather than typical analyst offers.[17][1]

Where the Opportunities Are Concentrated

Real opportunity in Philadelphia is spread across a long tail rather than one dominant employer. We observed more than 125 postings across more than 75 companies over the last 90 days, and the employer mix is fragmented.[15][7] The most consistently active named employers in the sample included Deloitte, Vanguard Group, Matricstek Inc, PhillyTech.Co, CACI, Ernst & Young LLP, Capgemini, and Upenn, with about 40% of postings coming from enterprise employers.[16][29] The industry mix shows where analytics is being bought, not just built. Healthcare accounts for about 25% of sampled postings, followed by financial services and technology at about 15% each, then professional services or consulting and insurance at about 10% each.[3] That favors candidates who can connect Python and SQL work to regulated reporting, operations improvement, decision support, governance, or stakeholder-facing BI rather than only research-style modeling.[4][5][8] This is also a fairly office-anchored market. About 45% of sampled roles were on-site, about 45% hybrid, and about 10% remote, so candidates who can commute and work closely with business stakeholders have an advantage.[23]

• Healthcare analytics and operations (high): Healthcare is the largest local demand pocket at about 25% of sampled postings, which makes care-delivery reporting, operational analytics, and compliance-aware analysis especially relevant.[3]
• Financial services and insurance analytics (high): Financial services account for about 15% of sampled postings and insurance for about 10%, which supports demand for decision support, risk, governance, and metric-heavy reporting work.[3]
• Consulting, enterprise BI, and governance (moderate): Professional services or consulting make up about 10% of sampled postings, Comcast has shown active BI and governance hiring, and enterprise employers represent about 40% of the sample.[3][8][29]

Where to focus: Focus first on enterprise and regulated-industry roles where Python, SQL, BI, and business communication solve real operating decisions, especially in healthcare and finance.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 65% of sampled local postings, making it the clearest baseline tool across analyst, data science, and AI-flavored roles.[4]
• SQL (table stakes): SQL shows up in about 45% of sampled local postings and is still the fastest way to prove you can work with real business data.[4]
• Machine learning plus statistical analysis (differentiator): Machine learning appears in about 30% of sampled local postings, while statistical analysis is also explicitly requested, so this combo helps you stand out beyond reporting-only work.[4]
• BI, data modeling, and business partnering (differentiator): Local postings ask for data visualization, and national pay guidance points to stronger compensation for analysts who combine BI, data modeling, and business partnering skills.[4][5]
• Snowflake and data governance (premium): Recent Philadelphia-area Comcast roles specifically signaled demand for Snowflake and data governance, which is unusually useful local evidence because it ties the skill to active named hiring.[8]
• AI governance, explainability, and fairness (differentiator): 2026 market guidance points to rising pressure around responsibility, transparency, fairness, and explainability in AI systems, which matters in healthcare, finance, and other regulated settings.[27][28]
• AWS machine learning or solutions architect certifications, plus Azure AI-102 as a structured learning path (differentiator): Explicit certification requirements are rare locally, with AWS certifications showing up in less than 5% of sampled postings, but a recognized credential can still help validate a technical transition, and a local program specifically prepares candidates for Azure AI-102.[6][22]

Adjacent Roles to Consider

• Business Operations Analyst or Revenue Operations Analyst (bridge): Local employers reward BI, data modeling, and business partnering, which maps well to operations-heavy analyst roles outside a formal data team.[5]
• Clinical Informatics or Healthcare Operations Analyst (both): Healthcare is the largest local demand segment at about 25% of sampled postings, so care-delivery, reporting, and workflow-improvement roles are a logical neighboring lane.[3]
• Risk, Fraud, or Insurance Analyst (both): Financial services and insurance together make up about a quarter of sampled local demand, and those functions value structured analysis, controls, and reporting discipline.[3]
• Marketing Analytics or CRM Analyst (bridge): A Philadelphia data-analyst role at Harmsworth Media circulated locally in July 2026, and this path uses the same SQL, dashboard, and experimentation muscles while sitting closer to growth teams.[24][4]

30 / 60 / 90-Day Plan

First 30 Days

• Split your search into two lanes, business-facing analyst or BI roles and advanced analytics roles, because the local market skews toward mid-level hiring and rewards clear positioning.[1][5]
• Rewrite your resume around the local baseline stack: Python, SQL, machine learning, data visualization, and statistical analysis.[4]
• Build two portfolio projects tied to the heaviest local demand pockets, one in healthcare and one in financial services or insurance.[3]
• Set alerts and networking targets around Comcast, Deloitte, Vanguard Group, CACI, Capgemini, Ernst & Young LLP, and Upenn because they were among the most consistently active named employers in the local sample.[16][8]

Days 31-60

• Add one governance-heavy case study using Snowflake-style tables, lineage assumptions, access controls, and an executive summary, because governance is showing up in active Philadelphia hiring.[8]
• Create a stakeholder-ready dashboard deck that explains a business decision, not just the analysis, to match the market's bias toward BI, modeling, and business partnering.[5]
• If you need a credential, choose one with signaling value for your path rather than collecting many; AWS certifications show up occasionally in local postings, while Azure AI-102 is a structured route for aspiring AI-track candidates.[6][22]
• Track every application by industry and work arrangement, and bias your effort toward healthcare, finance, insurance, and hybrid roles where the local mix is strongest.[3][23]

Days 61-90

• If interview flow is weak, widen to adjacent roles in operations, clinical informatics, insurance analytics, or marketing analytics instead of waiting only for ideal data scientist titles.[3][24]
• Prepare for slower hiring cycles by following up on roles that stay open for weeks; the typical active local posting has been open around 45 days.[25]
• For international candidates, prioritize employers or postings that explicitly mention sponsorship early, because only about 5% of sampled postings state visa sponsorship availability.[26]
• By this point you should have two resume versions, three portfolio pieces, and a target list of 25-40 hiring teams with tailored outreach rather than a high-volume spray approach.

Methodology and Confidence

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

Confidence: Overall confidence: Medium. Conclusions rely on a mix of direct local labor data and directional hiring proxies, and some sub-role conclusions require category-level inference.

Limitations

• The most precise local wage benchmark in this report is BLS pay data for data scientists from May 2024, so analyst, BI, analytics engineer, and AI-engineer pay in Philadelphia can sit above or below that anchor.[9]
• Statewide Data, Analytics & AI signals from Revelio Public Labor Statistics were used as a proxy where metro-level occupation data is not published for Philadelphia-Camden-Wilmington, PA-NJ-DE-MD.[10][11]
• The June 2026 metro unemployment, employment, and labor-force changes are preliminary and may be revised in later releases.[12][13][14]
• 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 here than exact counts or exact market shares.[15][16][4]
• Niche sub-roles, especially AI engineer and analytics engineer, have thinner local evidence than data scientist or data analyst, so some pay and competition conclusions for those tracks are inferred from broader posting and salary signals.[17][18]

References

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4. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
5. Robert Half. 2026 Data Analyst Salary Trends: What You Need to Know · 2025-10 · roberthalf.com
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7. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
8. Jobs. Search for Jobs in Global Media and Technology in a Career at Comcast · 2026-08 · jobs.comcast.com
9. Bureau of Labor Statistics. Occupational Employment and Wages in Philadelphia-Camden-Wilmington — May 2025 · 2025-03 · bls.gov
10. Reveliolabs. Employment — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
11. Reveliolabs. Job Openings — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
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13. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
14. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
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17. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
18. Salientinsights. Data & AI Salary Guide 2026: What US Employers Are Paying | Salient Insights · 2026-01 · salientinsights.com
19. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-07 · data.bls.gov
20. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.bls.gov
21. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
22. Nucamp. Top 10 AI Tech Bootcamps in Philadelphia, PA in 2026 · 2026-03 · nucamp.co
23. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
24. LinkedIn. 91+ Data Jobs Shared This Week (7/10/26) · 2026-07 · linkedin.com
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26. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
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28. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
29. Data. Data - warn_notice_layoff · 2026-07 · data.phillyburbs.com
30. Reveliolabs. Mass-layoff Notices — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
31. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
32. Reveliolabs. Salaries — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
33. Course. Data Analytics Salary 2026: Ranges by Role & Skills · 2026-01 · course.careers
34. Robert Half. 2026 Tech and IT Salaries and Compensation Trends · 2025-10 · roberthalf.com

Live Openings in This Market

This report is published monthly; its companion page tracks the active Data, Analytics & AI openings in Philadelphia-Camden-Wilmington, PA-NJ-DE-MD from the live Callings.ai job index. Browse current Data, Analytics & AI openings in Philadelphia-Camden-Wilmington, PA-NJ-DE-MD.