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Data Science Jobs in Rochester, MN (NOW HIRING)

Compeer Financial

Intern Data Analytics

Rochester, MN · On-site +1

$20 - $21/hr

Must be working towards completing a bachelor's or master's degree in Data Science, Computer Science, Economics, Mathematics, Statistics, Data Analytics or a related field. * Coursework or experience ...

Mayo Clinic

AI/ML Intern - Radiation Oncology

Rochester, MN · On-site

$15.25 - $19.75/hr

Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm ...

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All JobsData Science JobsData Science Jobs in Rochester, MN

Data Science information

See Rochester, MN salary details

$38.1K

$124.8K

$199.7K

How much do data science jobs pay per year?

As of Sep 11, 2026, the average yearly pay for data science in Rochester, MN is $124,763.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,100.00 and $138,200.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

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For Data Science jobs in Rochester, MN, the most frequently searched job titles are:

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The top searched job categories for Data Science jobs in Rochester, MN are:

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Cities near Rochester, MN with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Rochester, MN as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $124,763 per year, or $60 per hour.

Principal Data & Analytics Strategist

Rochester, MN • On-site

Mayo Clinic
Hospitals • 10K+ employees
Learn more about Mayo Clinicexternal

Full-time

Medical, Dental, Vision, Retirement

Re-posted 12 days ago

Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 707 frontline employees who took The Breakroom Quiz

Job description


The Principal Data Analytics & AI Strategist is a principal-level individual contributor who serves as a technical authority and enterprise-level thought leader for data, analytics, and AI solution direction across products, platforms, and strategic problem areas. This role shapes how enterprise data, analytics and AI strategy is translated into scalable solution patterns, architectural guardrails, and delivery models that can be consistently executed across teams.
The role connects system-level technical decisions to broader enterprise data and analytics strategy, governance, and investment intent-ensuring initiatives are interoperable, governable, and positioned to deliver sustained, measurable value at scale. The Principal Data Analytics & AI Strategist operates across high ambiguity, making and documenting complex tradeoffs related to platform capabilities, data architecture, analytics and AI patterns, operating constraints, and sequencing of delivery.
Working across domains and portfolios, the Principal Data Analytics & AI Strategist influences the full solution lifecycle-from opportunity framing and options analysis through solution design guidance and delivery oversight. The role defines and socializes reference architectures, preferred patterns, and decision frameworks, supports high-risk or high-impact initiatives, and accelerates progress through hands-on exploration and prototyping where early technical validation is critical.
The Principal Data Analytics & AI Strategist partners closely with senior leaders and practitioners across data engineering, analytics/BI, AI/ML, platform, security, and governance functions to align on technical direction, surface risks and dependencies early, and enable timely, enterprise-wide decision-making-exerting influence without direct authority to drive clarity, consistency, and execution momentum.
Qualifications
  • Bachelor's degree in computer science, information systems, engineering, mathematics, statistics, data science, or related field from an accredited University or College is required.
  • Master's degree or PhD in a related field (e.g., computer science, data science, business analytics, healthcare informatics, or MBA) is preferred.
  • Extensive (15-20+ years) experience in enterprise data, analytics, and/or AI strategy, architecture, consulting, product/program delivery, or related discipline.
  • Demonstrated experience defining enterprise-level strategy and translating it into executable roadmaps, capability models, and delivery guardrails across multiple portfolios.
  • Proven ability to communicate complex technical implementation concepts to executive leadership, including architecture tradeoffs, investment options, risk, and sequencing; produces clear, decision-ready materials.
  • Strong working knowledge of modern data and analytics concepts (data products, data platforms, pipelines, BI/visualization, governance, metadata, quality, privacy/security fundamentals, and observability).
  • Experience influencing across senior stakeholders and cross-functional teams (engineering, analytics, AI/ML, security, privacy, architecture, governance) to drive alignment and decisions in ambiguous environments.
  • Experience operating in regulated environments (e.g., healthcare, research, financial services), with familiarity with privacy, compliance, governance, and responsible AI expectations.
  • Demonstrated facilitation skills for executive and technical audiences (workshops, strategic reviews, governance forums) and strong written communication skills.
  • Certification in one or more major cloud platforms (Google, Azure, etc)
  • Experience establishing or evolving enterprise data operating models (e.g., data product operating model, platform governance, domain engagement, stewardship models) and measuring adoption/maturity over time.
  • Experience developing and/or governing enterprise AI strategy, including responsible AI controls, model risk management, and GenAI/agentic patterns (grounding, evaluation, monitoring).
  • Experience with cloud data platforms and modern architecture patterns (lakehouse/warehouse, streaming/eventing, semantic layers/metrics, MDM/reference data), including cost/value tradeoffs.
  • Demonstrated experience building reusable playbooks, reference architectures, templates, and standards that scale delivery across multiple teams.

The ideal candidate will have prior experience in working through large scale AI transformations for organizations including creation of vector stores, Knowledge graphs, MCP servers and getting an organization data teams AI ready.
About Us
Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.
Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.

About the Team
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.
Equal Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

What Mayo Clinic employees say

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About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919

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