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

Executive Verdict

Market rating: competitive | Confidence: High

Raleigh-Cary is a workable but selective market for Data, Analytics & AI right now. The metro unemployment rate was 3.1% in August 2026, total nonfarm employment was up 2.2338% year-over-year, and Professional and Business Services employment was up 2.9566% year-over-year, which is a supportive backdrop for hiring.[4][33][21] But the job search itself is not easy: the local sample showed more than 75 postings across more than 50 companies over the last 90 days, only about 10% were entry-level, and the mix skewed toward mid and senior hiring.[8][22] Statewide occupation signals also point to a higher bar rather than a broad boom, with Revelio Public Labor Statistics showing Data, Analytics & AI employment in North Carolina down 1.2% year-over-year even as active postings were up 43.8% year-over-year.[11][12]

Best positioned: The best odds right now belong to candidates who can show Python, SQL, machine learning, and business-facing analytics work, especially for consulting, banking, and healthcare teams.[10][2]

Main caution: The biggest mistake is treating Raleigh as an easy generalist market; remote roles are only about 20% of the sample, entry openings are scarce, and employers appear to be filling many openings with experienced hires.[9][22]

What Changed Recently

• Raleigh-Cary's unemployment rate eased to 3.1% in August 2026, and metro nonfarm employment reached 787.2 thousand, up 2.2338% year-over-year.[4][33]: The local economy is still expanding, so the main challenge is competition and fit, not a collapsing market.
• Local sector demand split further: Professional and Business Services employment grew 2.9566% year-over-year, while Information employment fell 6.7194% year-over-year in August 2026.[21][14]: Business-facing analytics roles look safer than searches aimed only at pure tech employers.
• Statewide occupation signals sharpen the picture: Revelio Public Labor Statistics shows North Carolina Data, Analytics & AI postings up 43.8% year-over-year while employment is down 1.2% year-over-year in September 2026.[12][11]: Expect more active openings and replacement hiring, but not a loose market where employers lower standards.
• Nationally, payroll growth was only 0.3128% year-over-year in September 2026, the unemployment rate was 4.2%, and the federal funds rate was 3.75%.[19][17][20]: The broader economy is still adding jobs, but slowly, so Raleigh employers can stay selective on tools, domain fit, and communication.

What This Means for You

Entry-Level Candidates

Difficulty: Hard: only about 10% of the local sample is entry-level, and most employers skew mid or senior.[22]

Best target: Target analyst-style openings in banking, healthcare, and consulting teams where SQL, Python, data analysis, and data governance matter more than publishing-grade ML depth.[2][10]

Biggest mistake: Applying as a generic 'AI enthusiast' without proof you can clean data, write SQL, and explain decisions to nontechnical stakeholders.[10][32]

Next step: Build two portfolio pieces in the next month: one SQL-heavy business analysis and one Python-based automation or modeling project with a short executive summary.

Mid-Career Candidates

Difficulty: Moderate but competitive: the metro backdrop is healthy, yet employers are using openings selectively rather than hiring loosely.[33][21][11][12]

Best target: Aim at decision science, applied ML, governance, and analytics-lead roles inside consulting, banking/lending, healthcare, and software companies.[2][10]

Biggest mistake: Sending the same résumé to every employer instead of translating your work into domain outcomes such as risk reduction, revenue lift, operations speed, or compliance.

Next step: Create separate résumé versions for consulting, regulated-industry analytics, and product or software contexts, each with different impact bullets and examples.

Career Switchers

Difficulty: Harder than it looks: remote roles are only about 20% of the sample, sponsorship is rare, and employers still want evidence of hands-on delivery.[9][15]

Best target: Switch through adjacent business-facing roles that use SQL, dashboards, experimentation, governance, or reporting rather than jumping straight to research-style AI titles.[10][32]

Biggest mistake: Overinvesting in standalone prompt-engineer branding when the skill is being absorbed into broader AI and analytics roles.[34]

Next step: Reframe your past work into measurable decision support, reporting, forecasting, or process-improvement outcomes, then add one modern AI-assisted workflow example that still shows human validation.

Salary Reality

high pay highly concentrated

Official local pay anchors are strong but title-specific: BLS lists Raleigh-Cary data scientists at a $120,710 median, $85,220 at the 25th percentile, and $145,500 at the 75th percentile in 2025.[23][24][25] A smaller, higher-end research-style niche pays more: computer and information research scientists were at a $128,370 median and $143,710 mean locally, but only 280 jobs were counted.[26][27][28] Current posting-based pay is directionally similar but broader, with listed salary ranges centered on about $105k to $175k and a broader 25th-75th band of about $96k to $192k.[29]

This is a well-paying metro for quantitative work: computer and mathematical occupations accounted for 5.9% of local employment versus 3.4% nationally in May 2025.[1]

The pay upside is offset by selectivity: only about 10% of openings are entry-level, about 55% are on-site, and state occupation data points to more openings without matching headcount expansion.[22][9][11][12]

Best-paying path: The strongest pay tends to sit in data scientist, research-oriented AI, and data architecture work; local averages were $124,380 for data scientists, $143,710 for computer and information research scientists, and $133,280 for database architects.[1][27]

Caution: Do not overread top-end figures like the $180,850 90th percentile for data scientists or the $182,000 90th percentile for computer and information research scientists; those describe the upper tail, not the typical offer, and both rely on 2025 wage data.[30][31][1]

Where the Opportunities Are Concentrated

Real openings are spread across a long tail rather than one anchor employer. The local sample shows more than 75 postings across more than 50 companies over the last 90 days, and employer concentration is described as fragmented.[8][16] Named employers that recur include First Citizens, LexisNexis, Relx Plc, Deloitte, Worldwide, Google Inc, Epic Games, Inc., and Headwater Science.[3] The opportunity mix leans toward business-facing analytics rather than pure research labs. Within the sample, IT services and IT consulting account for about 20% of postings, software development about 15%, business consulting about 15%, healthcare about 10%, and banking and lending about 10%.[2] That lines up with Raleigh's broader labor picture: Professional and Business Services employment rose 2.9566% year-over-year even while metro Information employment fell 6.7194% year-over-year.[21][14] For most job seekers, the best bets are teams that tie data work to regulated or revenue-critical workflows such as risk, operations, governance, decision support, and applied ML, rather than broad 'AI innovation' searches.

• Consulting and enterprise services (high): IT services and consulting account for about 20% of the sample and business consulting about 15%, with Deloitte among the recurring employers.[2][3]
• Banking and lending analytics (high): Banking and lending make up about 10% of the sample, and First Citizens is one of the recurring hirers, which is a good fit for risk, governance, and decision-support profiles.[2][3]
• Healthcare and life-sciences analytics (moderate): Healthcare is about 10% of the sample, offering a path for candidates with reporting, operations, or compliance-heavy backgrounds.[2]
• Pure tech and remote-first bets (limited): Software development is about 15% of the sample, but metro Information employment was down 6.7194% year-over-year and only about 20% of openings are remote.[2][14][9]

Where to focus: Prioritize business-facing analytics roles inside consulting, banking, and healthcare before chasing pure-play AI brand names.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 50% of local postings and is the common base for analytics, ML, and automation work.[10]
• SQL (table stakes): SQL shows up in about 40% of postings, and 2026 reporting says AI is automating query drafting, which raises the bar toward validating outputs and using SQL in business context.[10][35]
• Machine learning (premium): Machine learning appears in about 30% of local postings, and AI and machine learning were the most frequently cited skills gap nationally in one Robert Half survey at 45%.[10][36]
• Data governance (differentiator): Data governance appears in about 20% of local postings, which fits Raleigh demand in banking, healthcare, and consulting-heavy environments.[10][2]
• Prompt engineering and AI fluency (differentiator): Prompt engineering appears in about 20% of local postings, but the stronger signal is broader AI fluency because standalone prompt-engineer titles are fading into wider AI roles.[10][34]
• Stakeholder communication and model validation (premium): 2026 employer commentary points to critical thinking, business context translation, stakeholder communication, and model validation as the higher-value layer on top of tool use.[32][37]
• CDMP-P (differentiator): CDMP-P is the certification most often named locally, but it appears in less than 5% of postings, so it helps most for governance-heavy data management roles rather than general analytics jobs.[38]

Adjacent Roles to Consider

• Business Systems Analyst (both): Raleigh-Cary had 4,530 computer systems analyst jobs with a mean annual wage of $114,280, and the work often rewards SQL, requirements gathering, and process analysis.[1]
• Risk or Fraud Analyst (bridge): Banking and lending make up about 10% of the local sample, and First Citizens appears among the recurring employers, which creates a natural landing spot for SQL-heavy analytical talent.[2][3]
• Clinical Informatics Analyst (bridge): Healthcare accounts for about 10% of the local sample, giving healthcare-domain candidates a realistic way into data-adjacent work without competing head-on for pure AI titles.[2]
• Analytics-Focused Consultant or Strategy Analyst (pivot): Business consulting is about 15% of the local sample and Deloitte is one of the recurring employers, so some opportunities sit at the edge of analytics and business advisory work.[2][3]

30 / 60 / 90-Day Plan

First 30 Days

• Rewrite your résumé into three versions: consulting, regulated-industry analytics, and product or software analytics.
• Build two portfolio artifacts that look like real work: one SQL-based business analysis and one Python-based automation or modeling project with a short memo for a nontechnical reader.
• Replace any generic 'used AI' bullet with a workflow bullet that shows what you automated, what you still validated manually, and what business decision improved.
• Create a target list of local employers by segment instead of title alone, then rank them by domain fit, commute tolerance, and how closely your examples match their problems.

Days 31-60

• Publish two short writeups on LinkedIn or a personal site that show business framing, data cleaning choices, validation checks, and recommendation quality.
• Start a weekly outreach rhythm to alumni, former coworkers, and local practitioners with one sharp question about domain problems, not a generic request to chat.
• Practice interview stories around bad data, conflicting stakeholders, model or dashboard mistakes, and how you corrected them.
• If you want governance or enterprise data roles, begin CDMP-P prep; if you want applied AI roles, deepen one concrete workflow such as prompt evaluation, model validation, or retrieval-assisted analysis.

Days 61-90

• Expand your search to adjacent roles if direct analytics titles are not converting, especially systems analyst, risk analyst, healthcare informatics, or analytics consulting paths.
• Use response data to decide whether your blocker is title mismatch, domain mismatch, or seniority mismatch, then narrow rather than broadening further.
• Add one domain-specific case study in banking, healthcare, or operations so you are no longer presenting as a tool-generalist.
• If Raleigh opportunities are stalling, decide explicitly whether you will accept mostly on-site and hybrid work, because waiting only for remote roles will shrink your odds.

Methodology and Confidence

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

Confidence: Overall confidence: High. Recent local labor-market context is strong, but some occupation-specific pay and employment measures lag and statewide proxies were needed for part of the hiring picture.

Limitations

• Official local occupation wages and title counts come from the May 2025 wage release, so they are still the best pay anchor here but they lag the September 2026 job search market.[1]
• Several August 2026 local unemployment, employment, and labor-force readings are preliminary and may revise, so treat small month-to-month moves as directional rather than exact.[4][5][6][7]
• This category is broader than the data scientist title used in some government tables, so analyst, BI, governance, and ML-heavy roles are only partially captured by any single occupation series.[1]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so it is more reliable for recurring employer names, skill patterns, and work-arrangement mix than for exact market size or exact employer shares.[8][3][9][10]
• Statewide occupation data was used as a proxy where metro-level occupation hiring data is not published, so North Carolina occupation trends may overstate or understate conditions inside Raleigh-Cary itself.[11][12]

References

1. Bureau of Labor Statistics. Occupational Employment and Wages in Raleigh-Cary, NC — May 2025 : U.S. Bureau of Labor Statistics · 2026-07 · bls.gov
2. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
3. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
4. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
5. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
6. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
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11. Reveliolabs. Employment — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
12. Reveliolabs. Job Openings — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
13. Reveliolabs. Mass-layoff Notices — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
14. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
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16. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
17. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-09 · data.bls.gov
18. Federal Reserve Economic Data. Consumer Price Index for All Urban Consumers: All Items in U.S. City Average · 2026-08 · fred.stlouisfed.org
19. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-09 · data.bls.gov
20. Federal Reserve Economic Data. Federal Funds Effective Rate · 2026-09 · fred.stlouisfed.org
21. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
22. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
23. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
24. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
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27. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
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29. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
30. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
31. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
32. Wbscodingschool. AI skills: 5 competencies for your job security in 2026 · 2026-08 · wbscodingschool.com
33. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
34. Theaicareerlab. What Happened to the Prompt Engineer? (2026) · 2026-06 · theaicareerlab.com
35. Improvado. Will AI Replace Data Analysts? 2026 Reality Check · 2026-09 · improvado.io
36. Cio. State of IT jobs: AI sparks rapidly changing market for skills · 2026-02 · cio.com
37. Forbes. How AI Is Reshaping The Role Of The Data Analyst · 2026-07 · forbes.com
38. Callings.ai. Callings.ai job-market aggregation · 2026-09 · 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.