Is Data, Analytics & AI a Good Job Market in Raleigh-Cary, NC?

Executive Verdict

Market rating: competitive | Confidence: Medium

Raleigh-Cary is a competitive market for Data, Analytics & AI right now: the local sample shows more than 100 postings across more than 75 companies over the last 90 days, but the mix leans experienced rather than beginner-friendly.[17][6] Statewide, Data, Analytics & AI postings in North Carolina are up 27.9% year over year even as employment is down 0.8%, which points to live openings but tighter screening and slower net team growth.[11][10] Pay is attractive: BLS puts Raleigh data scientists at a mean annual wage of $124,380, and local posted salary ranges center on about $105k to $175k.[1][3]

Best positioned: The best odds are for candidates with several years of experience who can show Python, SQL, machine learning, and business-facing delivery in consulting, banking, or healthcare environments.[7][12][6]

Main caution: The biggest trap is assuming high salary headlines mean easy access; only about 15% of sampled postings are entry level, less than 5% of postings that state a policy mention visa sponsorship, and top-end pay data reflects specialized senior roles rather than the whole market.[6][20][5]

What Changed Recently

• North Carolina Data, Analytics & AI postings are up 27.9% year over year in July 2026, while statewide employment in the field is down 0.8% year over year.[11][10]: That usually means there are real openings, but employers are being more selective about exact fit and may be backfilling or upgrading roles rather than broadly expanding teams.
• The local Raleigh-Cary sample shows more than 100 postings across more than 75 companies over the last 90 days, but only about 15% are entry level while about 45% are senior and about 10% are lead+.[17][6]: The market is active, but it is tilted toward proven operators rather than first-job candidates.
• Local demand now blends classic analytics with AI: Python appears in about 65% of postings, SQL and machine learning in about 35% each, prompt engineering in about 20%, and large language models in about 15%.[7]: A dashboard-only or spreadsheet-only profile is weaker than it used to be; employers increasingly want people who can analyze data and use AI tools in the workflow.
• National labor conditions are still expanding, but slowly: total nonfarm payrolls reached 158858 thousand in July 2026, up 0.1993% year over year, and the U.S. unemployment rate was 4.3% in April 2026.[8][9]: For Raleigh job seekers, that points to a market where requisitions still exist, but approvals and interview cycles are likely to stay cautious rather than fast.
• Nearby Triangle demand is still visible in business-facing analytics, including a senior advanced-data-analytics role at Fidelity Investments in Durham and at least one Raleigh Business & Data Analytics opening at UnitedHealth Group.[14][15]: If pure AI titles feel too narrow, finance and healthcare analytics remain practical local lanes to pursue.

What This Means for You

Entry-Level Candidates

Difficulty: High. Only about 15% of sampled postings are entry level, so you are competing for a small share of the market.[6]

Best target: Target analyst and reporting roles in government, healthcare analytics, and banking-lending teams, where business use cases are clearer and the local market shows active demand.[12][2][15]

Biggest mistake: Applying straight into senior data scientist or AI engineer titles without a portfolio that proves SQL, Python, and stakeholder-ready analysis.

Next step: Build two portfolio pieces in the next month: one SQL-plus-dashboard case study and one Python analysis that uses an AI-assisted workflow and explains the business decision.

Mid-Career Candidates

Difficulty: Moderate. The market is more favorable for experienced candidates because about 45% of sampled roles are senior and about 10% are lead+.[6]

Best target: Aim at business-facing analytics, decision support, and applied ML roles in consulting, banking, technology, and healthcare rather than only pure research AI jobs.[12][7]

Biggest mistake: Leading with tools alone instead of showing measurable outcomes such as forecasting accuracy, revenue lift, risk reduction, or operating-cost savings.

Next step: Rewrite your resume around 3-5 quantified wins and create separate versions for consulting, finance, and healthcare employers.

Career Switchers

Difficulty: Moderate to high. Raleigh has openings, but the mix is selective and increasingly expects proof of hands-on technical work.[11][6][7]

Best target: Bridge into adjacent analytics roles where your domain knowledge matters, especially healthcare operations, banking risk, or public-sector reporting.[12][2][15]

Biggest mistake: Presenting yourself as 'passionate about data' without shipped work, a clear domain story, or evidence that you can use Python and SQL in real tasks.

Next step: Choose one target domain, convert a past work problem into an analytics case study, and package it as a hiring-ready project with stakeholder narrative, visuals, and code.

Salary Reality

high pay highly concentrated

Observed local pay anchors are solid but uneven. BLS shows Raleigh data scientists at a mean annual wage of $124,380, while the City of Raleigh lists Data Analyst at $66,400 to $102,900 and Senior Data Analyst at $73,100 to $113,300.[1][2] Proxy signals run higher for much of the current market mix: local posted ranges center on about $105k to $175k, North Carolina's mean offered salary on new Data, Analytics & AI openings was ~$116,501 in July 2026, and senior Raleigh data scientists show $196,000 median total compensation on Levels.fyi.[3][4][5]

This is a market where solid pay exists across the category, but the best compensation is concentrated in experienced, technical, and domain-specific roles rather than generic analyst work.

The upside is offset by selectivity. Entry-level roles are a small share of openings, and many of the highest-paying postings are tied to seniority, ML depth, or employer-specific compensation structures.[6][5]

Best-paying path: The strongest pay tends to sit in senior data scientist and AI-heavy roles, especially where machine learning, large language models, and PyTorch show up alongside business impact expectations.[5][7]

Caution: Do not read one pay number as the whole market. The BLS wage is for metro data scientists only, city salary bands reflect public-sector roles, posted ranges reflect the mix of recent openings, and the $196,000 figure is a senior total-compensation estimate rather than a typical analyst salary.[1][2][3][5]

Where the Opportunities Are Concentrated

The real opportunity in Raleigh-Cary is spread across a long list of employers rather than one dominant hirer. The local sample shows more than 100 postings across more than 75 companies over the last 90 days, and hiring is described as fragmented. Named employers showing repeated activity include First Citizens, LexisNexis, Matricstek Inc, YO IT Consulting, Relx Plc, Deloitte, and Provectus.[17][13][22] Industry concentration matters more than title chasing here. In the local sample, the biggest slices come from IT services and consulting at about 25%, technology at about 20%, software development at about 15%, banking and lending at about 15%, and healthcare at about 10%.[12] Nearby examples reinforce that pattern: Fidelity Investments posted a senior advanced-data-analytics role in Durham, and UnitedHealth Group still showed at least one Raleigh Business & Data Analytics opening in August 2026.[14][15] That means the best opportunities are not only in flashy AI titles. Raleigh rewards candidates who can connect analytics to regulated, business-facing workflows in finance, healthcare, and enterprise services, while public-sector paths remain a steadier but lower-paying option.[2][12]

• Consulting and tech-delivery analytics (high): IT services and consulting accounts for about 25% of sampled local postings, with recurring employer activity from Deloitte, Provectus, YO IT Consulting, and Matricstek Inc.[12][13]
• Banking and lending analytics (high): Banking and lending represents about 15% of the local sample, and First Citizens plus nearby Fidelity demand suggest room for decision support, risk, and insights work.[12][13][14]
• Healthcare analytics (moderate): Healthcare makes up about 10% of the local sample, and UnitedHealth Group still showed at least one Raleigh Business & Data Analytics opening, which supports continued demand for healthcare-focused analytics.[12][15]
• Public-sector analytics (moderate): The City of Raleigh maintains defined Data Analyst and Senior Data Analyst salary bands, which signals a clearer but lower-paying route for analysts who value stability and local mission work.[2]

Where to focus: Focus first on business-facing analytics roles in consulting, banking, and healthcare, and treat pure AI title searches as a second pass rather than your only strategy.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 65% of sampled local postings, making it the default screening skill across analysis, automation, and machine learning work.[7]
• SQL (table stakes): SQL shows up in about 35% of local postings and remains the clearest proof that you can pull, shape, and validate data in real business environments.[7]
• Machine learning (differentiator): Machine learning appears in about 35% of local postings, which is enough to separate candidates from pure reporting profiles.[7]
• Prompt engineering and LLM workflows (differentiator): Prompt engineering appears in about 20% of local postings and large language models in about 15%, while a 2026 study found 42.6% of employers asked students about AI skills during hiring.[7][29]
• PyTorch (premium): PyTorch appears in about 15% of local postings, which makes it a stronger signal for model-building and applied AI roles than for general analytics jobs.[7]
• AWS Certified Solutions Architect (differentiator): It is the most frequently mentioned certification in the local sample, even though it appears in only about 5% of postings, so it works better as a tie-breaker than as a core requirement.[30]
• Bachelor's degree (table stakes): Among local postings that specify education, a bachelor's degree is the most common requirement at about 50%, ahead of master's at about 20% and PhD at about 10%.[31]
• Domain fluency in banking, healthcare, or public-sector analytics (differentiator): Local demand is concentrated in consulting, banking and lending, and healthcare, while public-sector data roles remain visible through city pay bands and state-area openings.[12][2][15]

Adjacent Roles to Consider

• Business Analyst (bridge): It is a practical bridge because local demand is concentrated in business-facing sectors, and SQL plus data analysis remain common baseline skills in the sample.[12][7]
• Risk or Fraud Analyst (both): Banking and lending accounts for about 15% of the local sample, with First Citizens and nearby Fidelity reinforcing finance-oriented analytics demand.[12][13][14]
• Clinical Informatics or Healthcare Operations Analyst (both): Healthcare represents about 10% of the local sample, and UnitedHealth Group still showed a Raleigh Business & Data Analytics opening, making healthcare a credible local pivot lane.[12][15]
• Data Product Manager (pivot): By 2026, data product managers were identified as an emerging role, making product-oriented analytics a real neighboring path for candidates who like decision ownership more than pure modeling.[16]

30 / 60 / 90-Day Plan

First 30 Days

• Split your resume into two versions: one for business analytics and one for ML/AI, with different headlines, project bullets, and target employers.
• Build a short target list around consulting, banking, healthcare, and public-sector employers in the Triangle instead of searching only for 'data scientist.'
• Create one SQL-plus-dashboard case study and one Python notebook that shows analysis, automation, and a business recommendation.
• Add an AI workflow section to your portfolio that shows prompt design, output validation, and how you used an LLM to speed analysis without trusting it blindly.

Days 31-60

• Publish two polished portfolio artifacts with writeups: one operational analytics project and one ML or forecasting project.
• Reach out directly to hiring managers or team leads at named local employers and ask role-specific questions about business problems, not generic networking questions.
• Practice interview stories around measurable outcomes: revenue, cost, risk, utilization, turnaround time, or forecast quality.
• If you lack domain credibility, take one narrow domain sprint in finance, healthcare, or public policy and rebuild one project around that sector.

Days 61-90

• If response rates are weak, expand your target titles to Business Analyst, Risk Analyst, Clinical Informatics Analyst, and Data Product Manager.
• Use salary evidence to set a floor and a stretch band, then stop spending time on roles far below your acceptable range or far above your current scope.
• Audit your applications by segment and seniority; double down where interviews happen and stop mass-applying into senior AI roles if your profile is not converting.
• By the end of the period, have at least one employer-specific project or presentation ready for finance, healthcare, and consulting interviews.

Methodology and Confidence

This July 2026 report was generated on August 10, 2026. Latest direct national data: August 2026. Latest direct Raleigh-Cary, NC data: July 2026.

Confidence: Overall confidence: Medium. The core local picture is clear, but some conclusions require inference because the freshest metro occupation data lags the current hiring month.

Limitations

• The freshest metro occupation wage anchor here is May 2025 for data scientists, so the report relies partly on newer 2026 posting and salary proxies to describe current conditions.[1][3][15]
• Data scientist pay and employment should not be read as the pay or job count for every role in this broader category; Raleigh-Cary publishes stronger direct data for some titles than for others.[1][2]
• Statewide labor data was used as a proxy where metro-level occupation-by-month hiring data is not published, so North Carolina movement may not match Raleigh-Cary exactly.[10][11]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so it is more reliable for direction of demand, leading employer names, and skill patterns than for exact counts or exact market-share estimates.[17][13][7]
• Several recent local year-over-year government context figures are preliminary and may revise slightly, so treat tiny changes as directional rather than final.[23][24][25][26][27]

References

1. Bureau of Labor Statistics. Occupational Employment and Wages in Raleigh-Cary, NC — May 2025 · 2026-03 · bls.gov
2. Pub-raleighnc. Pub-raleighnc - entry_level_salary_range · 2025-06 · pub-raleighnc.escribemeetings.com
3. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
4. Reveliolabs. Salaries — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
5. Levels. Senior Data Scientist Salary in Raleigh, NC · 2025-09 · levels.fyi
6. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
7. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
8. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-07 · data.bls.gov
9. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-04 · data.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
12. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
13. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
14. Donewithwork. Data Analyst Jobs in North Carolina — 8+ Jobs | DoneWithWork · 2026-07 · donewithwork.com
15. Careers. Search our Job Opportunities at UnitedHealth Group · 2026-08 · careers.unitedhealthgroup.com
16. Radleyjames. How has the data science career path changed in 2026? - Radley James · 2026-08 · radleyjames.com
17. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
18. Wardandsmith. When the Layoffs Come: What North Carolina Employers Need to Know About the WARN Act | Ward and Smith, P.A. · 2026-06 · wardandsmith.com
19. Reveliolabs. Mass-layoff Notices — Revelio Public Labor Statistics (RPLS) · 2026-07 · reveliolabs.com
20. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
21. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
22. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
23. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
24. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
25. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
26. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
27. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-06 · data.bls.gov
28. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
29. American. American - ai_skills_hiring_increase · 2026-08 · american.edu
30. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai
31. Callings.ai. Callings.ai job-market aggregation · 2026-07 · callings.ai

Live Openings in This Market

This report is published monthly; its companion page tracks the active Data, Analytics & AI openings in Raleigh-Cary, NC from the live Callings.ai job index. Browse current Data, Analytics & AI openings in Raleigh-Cary, NC.