Is Data, Analytics & AI a Good Job Market in Minneapolis-St. Paul-Bloomington, MN-WI?

Executive Verdict

Market rating: competitive | Confidence: High

This is a competitive market over the next 3-6 months, not a shutdown market. Revelio Public Labor Statistics shows Minnesota Data, Analytics & AI active postings up 31.4% year over year in September 2026, but employment in the field down 1.3% over the same period.[6][7] In the metro, professional and business services employment rose 1.7696% year over year in August 2026 while information employment fell 7.0588%, so business-side analytics looks healthier than pure tech-facing teams.[24][15] The local sample still shows more than 150 postings across more than 50 companies over the last 90 days, but only about 5% of openings are entry level and about 60% are hybrid.[8][5][11]

Best positioned: Best odds go to mid-career or senior candidates who can pair Python and SQL with healthcare, retail, or enterprise analytics experience, especially in hybrid roles.[25][12][11]

Main caution: Do not mistake higher posting volume for an easy market; the local mix is senior-heavy and the typical active posting has been open around 28 days, which means employers are being choosy rather than desperate.[5][37]

What Changed Recently

• Minnesota's Data, Analytics & AI market is showing a split signal: active postings are up 31.4% year over year in September 2026, while employment in the field is down 1.3% year over year.[6][7]: That usually means more open searches than a year ago, but not a broad-based hiring wave yet.
• Inside the metro economy, professional and business services employment rose 1.7696% year over year in August 2026, while information employment fell 7.0588%.[24][15]: For job seekers, that tilts the odds toward analytics roles tied to operations, consulting, healthcare, finance, and enterprise reporting rather than pure tech-sector bets.
• The local ecosystem added several fresh AI signals: the University of Minnesota proposed a $10 million AI Talent and Innovation Hub, later announced a Workforce Development Accelerator and AI-in-education initiative, and the Metropolitan Airports Commission named an assistant director of data and artificial intelligence in October 2026.[32][33][34]: These do not guarantee immediate openings, but they do suggest more local demand for practical analytics, data governance, and AI adoption skills.
• September brought two local WARN notices: Pearson's Candy Company announced 80 affected employees beginning September 28, 2026, and Medtronic announced 6 affected employees beginning November 24, 2026.[13][14]: These notices are not data-role specific, but they are a reminder to vet employer stability and business unit momentum before accepting an offer.
• The national backdrop is steady but selective: unemployment was 4.2% in September 2026, nonfarm payrolls were up 0.3128% year over year, average hourly earnings were up 3.0%, CPI was up 3.0% in August, and the federal funds rate sat at 3.75%.[19][20][22][21][23]: That mix supports continued hiring, but it also explains why Minneapolis employers can keep salary discipline and raise the bar on experience.

What This Means for You

Entry-Level Candidates

Difficulty: Hard.

Best target: Business-facing analyst roles inside healthcare, payer/provider, retail, or enterprise reporting teams rather than AI engineer branding.

Biggest mistake: Applying straight into senior data science or ML-flavored roles without a portfolio that proves Python, SQL, and stakeholder communication.

Next step: Build two polished case studies in the next month: one dashboard/reporting project and one predictive or optimization project tied to a real business problem.

Mid-Career Candidates

Difficulty: Moderate.

Best target: Senior analytics, decision science, BI, and applied data science roles where domain context matters as much as modeling depth.

Biggest mistake: Leading with tools instead of business outcomes, especially if your resume reads like a technical inventory.

Next step: Rewrite your resume and LinkedIn around measurable impact: margin, cost, forecast accuracy, retention, risk, throughput, or clinical/operational outcomes.

Career Switchers

Difficulty: Hard.

Best target: Analytics roles closest to your existing industry knowledge, such as healthcare operations, retail planning, finance, or supply chain reporting.

Biggest mistake: Trying to rebrand as an AI specialist without evidence that you can already solve smaller analytics problems well.

Next step: Use your current domain to your advantage: translate one past business problem into a data case study and one dashboard or model that an employer can review quickly.

Salary Reality

high pay highly concentrated

The strongest local wage anchor is data scientist pay in the metro: the annual 25th percentile was $94,750, the median was $129,780, and the 75th percentile was $162,950 in 2025 BLS data.[1][2][3] Recent posted pay across the broader Data, Analytics & AI sample centers on about $102k to $176k, with a broader band of about $92k to $211k; that posting sample is broader in titles and only covers jobs that disclosed compensation.[10]

This is a well-paid market relative to the local baseline: the broad computer and mathematical group averaged $54.52 per hour in the metro, versus $35.86 across all occupations.[4] Minnesota's mean offered salary on new openings for the broader field was ~$114,903 in September 2026, above the state's all-occupations offered salary of ~$65,553.[29]

The upside comes with a barbell market: about 45% of sampled openings are senior and about 20% are lead+, while only about 5% are entry level.[5] Hybrid work dominates and remote is a small share, so candidates seeking fully remote roles are competing for a narrower slice of the market.[11]

Best-paying path: Top-end pay tends to sit in senior data science, research-heavy AI, and leadership-leaning roles that combine Python, machine learning, generative AI, and cloud or MLOps skills.[12] The metro's annual 90th-percentile data scientist pay reached $195,530 in 2025.[30]

Caution: Do not read the highest figures as typical; this category mixes analysts, data scientists, AI specialists, and hourly contract work, and disclosed salaries skew toward employers willing or required to post pay.[10][31]

Where the Opportunities Are Concentrated

The clearest concentration is healthcare and payer/provider analytics. In the local posting sample, hospitals and health care account for about 30% of openings, health care services & hospitals another about 15%, and healthcare another about 10%; Optum is the most visibly active named employer with more than 30 postings, plus Optum, Inc. with around 10.[25][9] That lines up with broader headquarters signals pointing to UnitedHealth Group and other large local enterprises as recurring homes for analytics talent.[26] A second pocket is retail and consumer analytics. Retail accounts for about 15% of sampled openings, and major local employers associated with analytics hiring include Target and Best Buy.[25][26] A third pocket is enterprise BI, consulting, and public-sector modernization: business consulting contributes about 10% of sampled postings, metro professional and business services employment is up 1.7696% year over year, and the Metropolitan Airports Commission just created an assistant director of data and artificial intelligence role to lead enterprise data practice and AI use.[25][24][34]

• Healthcare and payer/provider analytics (high): Best fit for candidates who can show outcomes in claims, care operations, forecasting, risk, or workflow analytics.
• Retail and consumer analytics (moderate): Good fit for SQL-heavy analysts and decision scientists who can work on merchandising, pricing, supply, or customer behavior problems.
• Consulting, enterprise BI, and public-sector data modernization (moderate): Useful lane for candidates who can combine dashboards, governance, stakeholder management, and light AI adoption work.

Where to focus: If you need the shortest path to interviews, start with healthcare and retail-adjacent analytics teams that want Python, SQL, dashboards, and business translation in hybrid settings.[25][12][11]

Skills and Credentials Worth Pursuing

• Python (table stakes): Python appears in about 75% of sampled local postings, making it the default screening skill across analyst-to-AI roles.[12]
• SQL (table stakes): SQL shows up in about 40% of sampled local postings and is also called out as a core skill for Upper Midwest data roles.[12][35]
• Tableau / Power BI (differentiator): Dashboard tools are repeatedly listed among the most in-demand regional skills, especially for business-facing analytics work.[35]
• Machine learning and generative AI (premium): Machine learning appears in about 35% of sampled local postings and generative AI in about 25%, showing employers want more than reporting-only backgrounds.[12]
• AWS / cloud data tooling (differentiator): AWS appears in about 20% of sampled postings, and cloud fluency pairs well with enterprise data teams moving AI into production.[12]
• MLOps and CI/CD (premium): CI/CD appears in about 20% of postings and MLOps in about 15%, which is a sign that the better-paid roles expect deployment discipline, not just modeling.[12]
• AWS certification (differentiator): AWS certification is explicitly required in less than 5% of sampled postings, so it helps more as a differentiator than as a hard gate.[36]
• Healthcare or retail domain fluency (differentiator): Healthcare-related employers dominate the local mix and retail is the next clear cluster, so domain fluency can beat a generic portfolio.[25]

Adjacent Roles to Consider

• Business analyst (bridge): It keeps you close to data work while reducing the bar on advanced modeling.
• Operations or supply chain analyst (both): Many of the same SQL, dashboard, forecasting, and optimization habits transfer cleanly.
• Risk or fraud analyst (pivot): Strong fit for candidates with quantitative thinking who want a clearer business use case.
• Market research analyst (pivot): It uses analysis, experimentation, and storytelling, especially for candidates with dashboard and survey skills.

30 / 60 / 90-Day Plan

First 30 Days

• Build one portfolio case in healthcare or payer analytics and one in retail or operations analytics, because those sectors make up much of the local demand.[25]
• Rewrite your resume around Python, SQL, machine learning or generative AI, and measurable business outcomes; mirror the local keyword mix, not a generic "data enthusiast" profile.[12]
• Shortlist 25 target teams in healthcare, retail, consulting, and enterprise analytics, starting with employers already active in the region such as Optum, Target, UnitedHealth Group, and Best Buy.[9][26]
• Prepare a hybrid-ready interview narrative that shows how you work with stakeholders, because hybrid roles make up about 60% of the local sample.[11]

Days 31-60

• Add one production-minded project that includes version control, repeatable data prep, and a simple deployment or handoff story so you are not filtered out of MLOps-leaning screens.[12]
• Attend one Twin Cities event such as the Women in AI and Data Science Conference or the Saint Paul SQL AI App in a Day workshop, and leave with 10 targeted conversations and 3 follow-up emails.[27][28]
• For each application, tailor your examples to business outcomes in healthcare, retail, or enterprise operations rather than reusing one generic portfolio deck.
• If you are a career switcher, aim for roles that reward domain context first and advanced modeling second.

Days 61-90

• If interviews are thin, widen your search to adjacent business analyst, operations analyst, and risk analyst roles inside the same employers.
• Start applying to seniority-matched hybrid roles first, then expand to on-site roles to improve odds if location is not a hard constraint.
• Publish one short case study on how you used Python plus SQL plus a business-facing dashboard to drive a decision, and use it as a follow-up asset after interviews.
• For international candidates, prioritize employers with clear sponsorship policies early, because less than 5% of postings that state a policy mention sponsorship availability.[18]

Methodology and Confidence

This September 2026 report was generated on October 10, 2026. Latest direct national data: September 2026. Latest direct Minneapolis-St. Paul-Bloomington, MN-WI data: October 2026.

Confidence: Overall confidence: High. Recent local occupation, wage, and hiring signals point in a consistent enough direction to support a decision page.

Limitations

• Most local title-specific wage benchmarks here come from annual 2025 federal wage data, so September 2026 market conditions can move faster than the salary anchors shown.[1][2][3][4]
• This category bundles several different role shapes, from business-facing analysts to data scientists and AI-leaning specialists, so pay and competition vary sharply by title and seniority; in the local sample, only about 5% of openings are entry level while about 65% are senior or lead+.[5]
• Statewide monthly Data, Analytics & AI employment and posting trends were used as a proxy where metro-level occupation-by-month data is not published, so Minnesota direction may not map perfectly to the Twin Cities itself.[6][7]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so leading employer names, skill patterns, work arrangements, and salary bands are more reliable than exact counts or market-share estimates.[8][9][10][11][12]
• September WARN notices at Pearson's Candy Company and Medtronic were company-level notices, not occupation-specific cuts, so they should be read as local risk context rather than proof of analytics layoffs.[13][14]

References

1. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
2. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
3. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
4. Bureau of Labor Statistics. Occupational Employment and Wages in Minneapolis-St. Paul-Bloomington — May 2025 : U.S. Bureau of Labor Statistics · 2026-07 · bls.gov
5. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
6. Reveliolabs. Employment — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
7. Reveliolabs. Job Openings — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
8. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
9. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
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11. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
12. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
13. Content. SRRT - WARN REVISION - PEARSON'S CANDY COMPANY · 2026-09 · content.govdelivery.com
14. Content. SRRT - WARN - COMPANY - MEDTRONIC, INC. · 2026-09 · content.govdelivery.com
15. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
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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. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-09 · data.bls.gov
20. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-09 · data.bls.gov
21. Federal Reserve Economic Data. Consumer Price Index for All Urban Consumers: All Items in U.S. City Average · 2026-08 · fred.stlouisfed.org
22. Federal Reserve Economic Data. Average Hourly Earnings of All Employees, Total Private · 2026-09 · fred.stlouisfed.org
23. Federal Reserve Economic Data. Federal Funds Effective Rate · 2026-09 · fred.stlouisfed.org
24. Bureau of Labor Statistics. Bureau of Labor Statistics Data · 2026-08 · data.bls.gov
25. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
26. Greatermsp. Home - Minneapolis Saint Paul Economic Development | Greater MSP · 2026-01 · greatermsp.org
27. Siliconlakes. Where AI Builders, Founders and Leaders Meet · 2026-10 · siliconlakes.ai
28. Devblogs. Upcoming SQL and AI Events to Put on Your Calendar - Azure SQL Dev Corner · 2026-10 · devblogs.microsoft.com
29. Reveliolabs. Salaries — Revelio Public Labor Statistics (RPLS) · 2026-09 · reveliolabs.com
30. Bureau of Labor Statistics. Bureau of Labor Statistics Data · data.bls.gov
31. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
32. Twin-cities. University of Minnesota advances priorities to strengthen Minnesota’s workforce, innovation and economic competitiveness · 2026-09 · twin-cities.umn.edu
33. Twin-cities. University of Minnesota unveils bold new initiatives to strengthen Minnesota’s future · 2026-10 · twin-cities.umn.edu
34. Southwestvoices. Metropolitan Airports Commission names Nick Running as assistant director of data and artificial intelligence - Southwest Voices · 2026-10 · southwestvoices.news
35. Indeed Hiring Lab. Home - Indeed Hiring Lab · 2026-06 · hiringlab.org
36. Callings.ai. Callings.ai job-market aggregation · 2026-09 · callings.ai
37. 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 Minneapolis-St. Paul-Bloomington, MN-WI from the live Callings.ai job index. Browse current Data, Analytics & AI openings in Minneapolis-St. Paul-Bloomington, MN-WI.