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Data Scientist Machine Learning Jobs in Minnesota

Data Scientist

Minnetonka, MN · Remote

$60K - $107K/yr

The team is a blend of AI/ML engineers, data scientists, data engineers, and GenAI specialists who ... Develop traditional machine learning models (classification, anomaly detection, NLP pipelines) for ...

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 ...

Candidate has expertise in AI, machine learning, deep learning, statistical data processing ... scientist. Other responsibilities: Provides data insights for business problems that can be ...

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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 Jul 17, 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 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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, 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:
What are popular job titles related to Data Scientist Machine Learning jobs in Minnesota? For Data Scientist Machine Learning jobs in Minnesota, the most frequently searched job titles are:
Infographic showing various Data Scientist Machine Learning job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% 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.
Senior Director, Applied AI & Data Science - Hybrid in MN

Senior Director, Applied AI & Data Science - Hybrid in MN

UnitedHealth Group

Minnetonka, MN • Hybrid

Full-time

Retirement

Posted 7 days ago

New


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

191st of 886 rated healthcare providers


Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

The Senior Director, Applied AI & Data Science is a strategic business and technology leader responsible for identifying, shaping, and delivering AI-driven transformations across the Medicare & Retirement business. This role partners closely with senior business leaders to uncover high-impact opportunities where AI [Data Science, Machine learning and Agentic AI ] can materially improve cost, operational efficiency, and member outcomes, and to translate those opportunities into funded, enterprise-scale initiatives.

This leader curates and prioritizes a portfolio of AI use cases, defines clear value propositions and success metrics, and builds executive-ready proposals grounded in business value, risk, and feasibility. The role requires strong executive presence to influence investment decisions, secure funding, and champion initiatives from concept through approval and scaled delivery.

  This position follows a hybrid schedule with four in-office days per week.

 

Primary Responsibilities:

  • Define and lead AI/ML strategy for Medicare & Retirement, driving end-to-end AI enabled software delivery aligned to business transformation with measurable outcomes
  • Partners with business leaders to identify and shape high impact opportunities where AI can drive transformative outcomes. Develops executive ready use cases with clear value propositions and presents them to senior leadership to secure alignment and funding
  • Requires strong business acumen, executive presence, and the ability to position AI as a lever for transformation-not just technology
  • Own end-to-end lifecycle delivery of Software Engineering - from problem framing and design through development, deployment, scaling, and optimization of production grade Data Science, Machine learning and Agentic AI solutions
  • Provide end-to-end technical leadership for building AI-native applications integrating AI/ML within core application architecture, data strategy, model development, and develop core products, ensuring scalable, secure, and resilient production-ready systems
  • Embed responsible and secure AI practices across the delivery lifecycle, including governance, fairness, transparency, compliance, and adherence while adhering to enterprise security standards
  • Build and lead high performing greenfield AI engineering teams, fostering a culture of innovation, continuous learning, team mentorship and engineering excellence
  • Partner cross-functionally across product, finance, compliance, infrastructure, security, and business leaders to deliver integrated, enterprise-aligned AI solution
  • Communicate AI strategy, delivery progress, and business impact with clarity and executive presence to senior leadership and board level stakeholders

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

  • 15 years in IT industry with Master's degree in Statistics, Computer Science, Mathematics, Data Science, or a related discipline 
  • 8 years of enterprise leadership experience defining strategy, architecture, and delivery across multiple teams
  • 4 years in Senior Director / VP level positions, leading largescale applied AI/ML engineering organizations (30 to100 team consisting of engineers, data scientists, and ML engineers, across shores) delivering Data Science, Machine learning and Agentic AI solutions end-to-end production software platforms 
  • Proven success building and operating AI enabled software products, from full stack application development to AI/ML integrated solution with $15M annual budgets in healthcare or similarly regulated environments
  • Proven solid business acumen with ability to link AI investments to ROI, risk, and strategic outcomes
  • Demonstrated executive communication skills and ability to influence funding and prioritization decisions
  • Ability to work a Hybrid schedule in Minnetonka, MN

Preferred Qualifications:

  • Deep domain expertise in healthcare and regulatory frameworks
  • Solid understanding of Medicare regulatory needs including data governance, privacy, and HIPAA compliance
  • Proficiency in solving combinatorial optimization challenges through AI, and integrating them into mainstream solutions
  • Demonstrated success in scaling GenAI and enterprise-grade ML capabilities across large enterprises

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 - $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

 

 

Diversity creates a healthier atmosphere: UnitedHealth Group is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.

 

UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.


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