Is Data, Analytics & AI a Good Job Market in Seattle-Tacoma-Bellevue, WA?

Executive Verdict

Market rating: competitive | Confidence: High

Seattle is still a real market for data and AI, but it is not an easy one. The metro shows more than 300 sampled postings across more than 125 companies in the last 90 days, while metro unemployment was 4.8% in August 2026 and total nonfarm employment was up 0.8752% year over year.[8][7][45] At the same time, Revelio Public Labor Statistics shows Washington data, analytics & AI postings up 32.1% year over year while statewide employment in the field was down 1.0%, which points to strong employer interest but a tougher race for each opening.[10][9]

Best positioned: Your best odds are if you already have 3-8 years of experience, can work on-site or hybrid, and can show Python, SQL, and machine-learning work tied to business outcomes, because the sampled market is about 45% mid-level, about 35% senior, and heavily asks for those skills.[29][13][14]

Main caution: The biggest trap is assuming Seattle's salary headlines mean broad access; only about 10% of sampled postings are entry-level and only about 5% are remote.[29][13]

What Changed Recently

• Washington's field-specific data, analytics & AI postings were up 32.1% year over year in September 2026, even as field employment was down 1.0% statewide.[10][9]: That is a sign of active requisitions, but not a simple hiring boom; expect more competition, recycled openings, and slower closes than the posting count alone suggests.
• Seattle-Tacoma-Bellevue unemployment was 4.8% in August 2026 and unchanged year over year, while metro nonfarm employment was up 0.8752% year over year.[7][45]: The local backdrop is steadier than many tech workers assume, so the market is not frozen, but employers still have room to be selective.
• The local opening mix is still tilted away from beginners: about 10% entry, about 45% mid, about 35% senior, and about 10% lead+.[29]: If you are junior, a generic resume is unlikely to work; you need proof of applied analysis, stakeholder communication, and AI-assisted workflow judgment.
• September brought fresh Seattle AI-company expansion signals: Nuance Labs said its $50 million Series A would support hiring across modeling, data, evaluation, and real-time serving; Augmeta said it was hiring after a $3 million seed round; Meadow AI said it would expand engineering, product, and go-to-market after a $7 million seed round.[30][31][32]: Some of the most interesting local openings may come from younger firms and applied-AI teams, not just the usual big-tech employers.
• National unemployment was 4.2% in September 2026, CPI was up 3.0% year over year in August 2026, and the federal funds rate was 3.75% in September 2026.[22][25][26]: That mix usually means a cooler but functioning hiring market: employers can still fund specialized data hires, but they screen harder on business impact and near-term productivity.

What This Means for You

Entry-Level Candidates

Difficulty: Harder than usual, because only about 10% of sampled postings are entry-level and most openings sit at mid or senior levels.[29]

Best target: Target analyst and BI-adjacent roles where you can show one strong business case study, one dashboard story, and one AI-assisted analysis workflow; the market most often asks for Python, SQL, machine learning, and data visualization.[14]

Biggest mistake: Leading with coursework, certificates, or generic dashboards instead of a clear business problem you solved.

Next step: Build two portfolio pieces in the next month: one SQL/Python analysis tied to a business decision and one dashboard with a written QA section showing how you checked AI-generated output.

Mid-Career Candidates

Difficulty: Good but competitive, because about 45% of sampled openings are mid-level and another about 35% are senior.[29]

Best target: Aim at tech, research, retail, and product teams where you can connect experimentation, forecasting, or model work to revenue, customer behavior, or operations; those are the industries showing the clearest local concentration.[36]

Biggest mistake: Applying as a generic 'data professional' instead of packaging yourself around a business domain, decision type, and measurable outcomes.

Next step: Rewrite your resume into two versions: one for analytics/decision roles and one for ML/AI roles, each with metrics, experimentation language, and examples of stakeholder-facing communication.

Career Switchers

Difficulty: Difficult unless you bring directly transferable domain context, because the market skews toward bachelor's-or-higher roles and rarely treats certifications as a substitute.[43][44]

Best target: Make the move through business-side analytics, reporting, metrics, or governance-heavy work where your domain knowledge can matter as much as pure modeling depth.

Biggest mistake: Trying to jump straight into 'AI engineer' positioning without a track record in analysis, experimentation, model evaluation, or data quality.

Next step: Pick one industry you already understand, build a domain-specific case study around it, and use that to pursue business analyst, BI, governance, or analytics translator roles first.

Salary Reality

high pay highly concentrated

For a hard local anchor, BLS puts Seattle data scientists at $108,740 at the 25th percentile, $164,740 at the median, and $210,370 at the 75th percentile in 2025.[37][5][38] Higher-end research-heavy AI roles proxy even above that: computer and information research scientists were at $153,130 at the 25th percentile and $211,270 at the median.[39][6] More current sampled postings center on about $136k to $198k locally, while Revelio Public Labor Statistics shows a Washington mean offered salary on new openings of about $136,742 in September 2026 (n=1,329).[40][11]

This is a high-pay market by national standards: the national median for data scientists was $120,230 in 2025, well below Seattle's $164,740 local median.[41][5] But Seattle pay is buying into a market where housing is still expensive even after the Seattle home price index was down 2.1% year over year in July 2026.[42]

The tradeoff is access. Only about 10% of sampled openings are entry-level, about 60% are on-site, and about 30% are hybrid, so high pay comes with experience and location filters.[29][13]

Best-paying path: The best-paying path tends to be ML, AI, and research-heavy work rather than general reporting, especially in large tech or advanced product teams.[39][6][12]

Caution: Do not read top-end wage figures as the typical Seattle offer. Government wage estimates lag to 2025, the category includes several sub-roles with different pay bands, and live posting ranges are broader and noisier than occupation medians.[40][5][6]

Where the Opportunities Are Concentrated

Real opportunity is concentrated where Seattle already over-indexes in technical work. BLS said computer and mathematical occupations made up 9.3% of Seattle-Tacoma-Bellevue employment in May 2025, versus 3.4% nationally.[50] In the sampled local data market, the most-active industries are software development at about 30%, technology at about 20%, research services at about 15%, internet & web services at about 10%, and retail at about 10%.[36] That means the best targets are not evenly spread across every employer type. The employer base is fragmented rather than winner-take-all, but the named leaders are still large platform employers—Amazon, Amazon Inc., Microsoft, and Campus Building—while the role mix skews to mid and senior talent.[18][12][29] If you insist on fully remote work, you are fishing in the smallest pond, because only about 5% of sampled postings are remote.[13] The second pocket is venture-backed applied AI. In September alone, Nuance Labs, Augmeta, and Meadow AI all linked fresh funding to planned team expansion, and Databricks continued integrating a Seattle acquisition into its local office footprint through the Row Zero deal.[30][31][32][33]

• Large platform employers (high): Still the most visible pool, led by Amazon and Microsoft in the local sample, but competition is strongest and the roles skew mid-to-senior.[12][29]
• Applied analytics in retail and business services (moderate): Retail accounts for about 10% of sampled category demand locally, and metro professional and business services employment was up 0.6278% year over year in August 2026.[36][27]
• Venture-backed AI and data startups (moderate): Smaller absolute volume, but recent Seattle funding rounds at Nuance Labs, Augmeta, and Meadow AI point to fresh team build-outs.[30][31][32]

Where to focus: Focus first on mid-level, on-site or hybrid roles in tech, research, retail, and venture-backed AI teams where your work can be tied to revenue, experimentation, forecasting, or model evaluation.

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 75% of sampled local postings, making it the clearest baseline filter in this market.[14]
• SQL (table stakes): SQL shows up in about 60% of sampled local postings and remains the fastest way to prove you can work with production data, not just notebooks.[14]
• Machine learning (premium): Machine learning is requested in about 40% of sampled local postings, and broader Seattle skill signals also list it among the most in-demand tools for data analysts and data scientists.[14][46]
• Power BI / data visualization (differentiator): Data visualization appears in about 15% of sampled local postings, and broader Seattle skill signals specifically name Power BI among in-demand tools.[14][46]
• AI governance and data governance (premium): Quality control and governance are becoming core analyst responsibilities as AI generates more insights, and AI governance is one of the specialized skills tied to compensation upside.[2][3]
• Prompt engineering and AI-assisted analysis workflow (differentiator): Prompt engineering is becoming useful for data professionals, while AI tools are already handling routine SQL, cleanup, charting, and report-drafting tasks.[47][48]
• Google Professional Machine Learning Engineer Certification (differentiator): Local postings most often specify no certification, with none specified in less than 5% of sampled postings, so this is not table stakes; it helps mainly as a depth signal for production ML work.[44][49]

Adjacent Roles to Consider

• Business Analyst / Analytics Translator (bridge): As AI automates routine query and reporting work, the value of problem framing, stakeholder communication, and validating outputs against business reality rises.[1][2]
• Data Governance / AI Governance Analyst (both): Governance and quality control are becoming core analyst responsibilities, and AI governance is one of the specialized skills tied to compensation.[2][3]
• AI Assurance & Validation Specialist (pivot): It is one of the emerging career archetypes at the intersection of data and generative AI.[4]
• Business Intelligence Developer (both): It stays close to SQL, semantic modeling, and dashboard work, and Robert Half puts the U.S. midpoint at $134,750 for 2027.[3]

30 / 60 / 90-Day Plan

First 30 Days

• Split your resume into two lanes: analytics/decision support and data science/AI. Do not send the same document to both.
• Build two portfolio pieces: one SQL/Python business analysis and one stakeholder-facing dashboard with a short write-up on assumptions, tradeoffs, and QA.
• Add a short 'AI-assisted workflow' section to your portfolio showing how you used AI tools, what they got wrong, and how you verified the output.
• Stop filtering for remote-only roles; widen your search to Seattle and Bellevue on-site and hybrid jobs because remote is only about 5% of the sampled market.[13]

Days 31-60

• Create two target-employer lists: established platform employers and Seattle venture-backed AI firms. Track hiring pages and recruiter movement weekly for Amazon, Microsoft, Databricks-adjacent teams, Nuance Labs, Augmeta, and Meadow AI.[12][30][31][32][33]
• Attend local AI networking events if you are in-region; Seattle AI Week was promoted with more than 100 community-hosted events across October 26-30, and New Tech Seattle scheduled an October 13 preview meetup.[34][35]
• Publish one short public artifact each month: a metrics memo, experiment review, or model-evaluation teardown aimed at a real business audience.
• If you are junior, start applying to BI, governance, and business-analytics roles alongside data scientist titles instead of waiting for a perfect match.

Days 61-90

• If response rates are weak, pivot explicitly into adjacent roles such as BI developer, analytics translator, or AI governance analyst instead of only applying to core data scientist titles.
• Build one domain-specific case study for retail, product, or operations analytics, because those are clearer local demand pockets than a generic capstone.[36]
• For ML-targeted paths, add one production-style project with evaluation, monitoring logic, and documentation before spending heavily on another course or certificate.
• If you are still stuck at the entry level, prioritize contract, hybrid, or analyst-to-BI pathways that let you accumulate shipped work quickly.

Methodology and Confidence

This September 2026 report was generated on October 10, 2026. Latest direct national data: September 2026. Latest direct Seattle-Tacoma-Bellevue, WA data: September 2026.

Confidence: Overall confidence: High. Based on 38 direct local occupation data points and 58 total local evidence items with recent coverage.

Limitations

• Local occupation pay anchors come mostly from 2025 wage files, while labor-market context and posting signals are current through August and September 2026, so compensation conditions can move faster than the headline wage tables show.[5][6][7][8]
• This category is broader than any one government occupation code; local wage anchors for data scientists and computer and information research scientists are useful, but they do not fully capture every Seattle BI, analytics-engineering, decision-science, or AI-facing role.[5][6]
• Statewide labor data was used as a proxy where metro-level Revelio Public Labor Statistics is not published, so Washington field-level hiring and salary signals may not match Seattle exactly.[9][10][11]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so it is better for direction of demand, leading employer names, work arrangements, and skill patterns than for exact counts or precise market share.[8][12][13][14]
• Several August 2026 unemployment, labor-force, and employment change figures are early estimates that can be revised in later releases, so small year-over-year moves should not be overread.[7][15][16][17]

References

1. Online. Future of Data Analyst Jobs in an AI-Driven World (2026) · 2026-07 · online.edgewood.edu
2. Improvado. Will AI Replace Data Analysts? 2026 Reality Check · 2026-09 · improvado.io
3. Robert Half. 2027 Technology salary trends: The skills and roles driving growth · 2026-09 · roberthalf.com
4. Spjain. How Generative AI Is Transforming Data Science Careers in 2026 · 2026-01 · spjain.org
5. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
6. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
7. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
8. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
9. Reveliolabs. Employment — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
10. Reveliolabs. Job Openings — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
11. Reveliolabs. Salaries — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
12. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
13. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
14. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
15. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
16. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
17. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
18. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
19. Reveliolabs. Mass-layoff Notices — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
20. Lynnwoodtimes. 600 Jobs Cut in Fresh WARN Filings as Unemployment Hits 5% - Lynnwood Times · 2026-09 · lynnwoodtimes.com
21. Downtownseattle. Recent Data Point to Shifting Employment Landscape in Seattle · 2026-09 · downtownseattle.org
22. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-09 · data.bls.gov
23. Federal Reserve Economic Data. Average Hourly Earnings of All Employees, Total Private · 2026-09 · fred.stlouisfed.org
24. Federal Reserve Economic Data. Consumer Price Index for All Urban Consumers: All Items in U.S. City Average · 2026-08 · fred.stlouisfed.org
25. Federal Reserve Economic Data. Federal Funds Effective Rate · 2026-09 · fred.stlouisfed.org
26. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
27. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
28. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
29. Geekwire. Seattle’s Nuance Labs raises $50M to give AI models human expression and nuance · 2026-09 · geekwire.com
30. Geekwire. Former Amazon and Opendoor leaders raise $3M to give every key business metric its own AI agent · 2026-09 · geekwire.com
31. Thesaasnews. Meadow AI Raises $7M Seed · 2026-09 · thesaasnews.com
32. Geekwire. Seattle startup Row Zero acquired by Databricks to bring enterprise spreadsheets to AI platform · 2026-09 · geekwire.com
33. LinkedIn. #seattleaiweek #seattletech #aisummit #techsummit #policy | WTIA · 2026-09 · linkedin.com
34. Newtechnorthwest. New Tech Northwest · 2026-09 · newtechnorthwest.com
35. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
36. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
37. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
38. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
39. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
40. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
41. Federal Reserve Economic Data. S&P Cotality Case-Shiller WA-Seattle Home Price Index · 2026-07 · fred.stlouisfed.org
42. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
43. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
44. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
45. Askmetraining. You are being redirected... · 2026-09 · askmetraining.in
46. Kissmetrics. Will AI Replace Data Analysts? The Honest 2026 Answer · 2026-08 · kissmetrics.io
47. Ucertify. Top Machine Learning Certifications to Advance Your AI Career · 2026-07 · ucertify.com
48. Bureau of Labor Statistics. Occupational Employment and Wages in Seattle-Tacoma-Bellevue — May 2025 : U.S. Bureau of Labor Statistics · 2026-06 · bls.gov

Live Openings in This Market

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