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Data Scientist Machine Learning Jobs in Minnesota

Cargill

Senior Data Scientist

Wayzata, MN · On-site

$148K/yr

... Machine Learning (AI/ML) platforms, such as Amazon SageMaker, SAP IBP, and a custom time series ... manage data science initiatives in food supply chain planning, including scoping, development ...

New

Cargill

Senior Data Scientist

Wayzata, MN

$148K/yr

... Machine Learning (AI/ML) platforms, such as Amazon SageMaker, SAP IBP, and a custom time series ... manage data science initiatives in food supply chain planning, including scoping, development ...

New

DeFiner Inc

Create machine learning solutions for a diverse set of business problems. * Employ structured ... data science solutions. * Present and defend results to leadership audiences, both technical and ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Minnesota

Data Scientist Machine Learning information

See Minnesota salary details

$36.7K

$120.2K

$192.5K

How much do data scientist machine learning jobs pay per year?

As of Jun 26, 2026, the average yearly pay for data scientist machine learning in Minnesota is $120,211.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,500.00 and $133,200.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is ML a high paying job?

Data Scientist Machine Learning roles are generally well-paid due to the specialized skills required, such as programming in Python or R and knowledge of algorithms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for expertise in machine learning and data analysis.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require advanced analytical skills, domain expertise, and the ability to interpret complex models. Jobs that involve creative thinking, emotional intelligence, and tasks requiring human judgment—such as healthcare professionals, educators, and skilled trades—are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Minnesota? The most popular types of Data Scientist Machine Learning jobs in Minnesota are:
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What job categories do people searching Data Scientist Machine Learning jobs in Minnesota look for? The top searched job categories for Data Scientist Machine Learning jobs in Minnesota are:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Minnesota as of June 2026, with employment types broken down into 82% Full Time, 7% Part Time, and 11% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,211 per year, or $57.8 per hour.
Data Scientist - Research Sovereign AI

Data Scientist - Research Sovereign AI

Mayo Clinic

Rochester, MN • On-site

Full-time

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.

Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

106th of 876 rated healthcare providers

Job description


Data Scientist Foundational Model Science
Position Summary
The Data Scientist for Foundational Model Science is the senior technical leader, and the lead scientist responsible for designing, training, and governing Mayo's multimodal foundational model. This model forms the core intelligence layer used by clinical departments, researchers, agentic workflows, and sovereign AI collaborations. The individual will work as a hands-on architect, model-builder, and researcher while acting as a player-coach, guiding strategy and building a future team.
Key Responsibilities
Scientific & Technical Leadership
  • Design multimodal foundational model architectures integrating signals from imaging, text, waveforms, structured data, graph representations, and temporal embeddings.
  • Develop fusion, alignment, and cross-modal reasoning mechanisms (early fusion, late fusion, token-level fusion, hybrid models).
  • Define and implement methods for grounded clinical reasoning, retrieval-augmented inference, graph-augmented attention, and chain-of-thought verification.
  • Establish protocols for model lifecycle governance, safe update cycles, drift-aware re-training, and provenance tracking.

Hands-On Modeling & Training
  • Train large-scale deep learning models, including multimodal architectures and domain-specific transformer-based systems, on real clinical datasets.
  • Fine-tune and adapt large language models (LLMs) for clinical reasoning, summarization, question answering, agentic behavior, and instruction-following tasks.
  • Build retrieval-augmented pipelines using embeddings, vector stores, graph traversal, and clinically grounded context construction.
  • Develop evaluation methods for reasoning quality, temporal prediction accuracy, multimodal synergy, ablation-based robustness, and counterfactual behavior.
  • Create reference-grounded training datasets, structured reasoning tasks, and multimodal benchmarks to evaluate model performance.
  • Conduct hands-on experimentation with optimization strategies, large-scale distributed training, model quantization, and inference acceleration.
  • Implement uncertainty modeling, selective prediction, abstention mechanisms, and clinically meaningful risk thresholds.
  • Build interpretable reasoning pathways, cross-modal attribution maps, and reference-grounded explanations.

Cross-functional Collaboration
  • Work closely with the Representation team to ensure representation-model alignment.
  • Partner with clinical SMEs to encode domain reasoning into reinforcement learning, preference optimization, or rule-guided behaviors.

Team Leadership
  • Serve as the future founding technical lead of the Foundational Model Science Program.
  • Mentor scientists and engineers and eventually build a specialty modeling team.

Qualifications
Required
  • PhD in Machine Learning, Computer Science, Applied Mathematics, or related discipline with at least four years of informatics, Artificial Intelligence, data science and/or machine learning.
  • Experience with generative modeling, reasoning models, or multimodal foundation models.
  • Expertise in alignment methods (contrastive learning, RLHF/RLCS, preference optimization).
  • Experience with distributed training, and large-scale compute.

Preferred
  • Experience with clinical or EMR data across multiple modalities.
  • 7+ years experience training deep learning models, including transformers or multimodal architectures.
  • Experience defining evaluation frameworks for reasoning, multimodal synergy, reliability, or fairness.
  • Publications in multimodal learning, foundation models, or reasoning architectures.

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.

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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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