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Remote Data Science Jobs in Minnesota (NOW HIRING)

Product Manager (Data Science)

Medina, MN · On-site +1

$140K - $160K/yr

You will serve as a Product Manager for Data Science, advancing enterprise Data & Analytics ... Ability to work in a remote or hybrid model while being commutable to Medina, MN for quarterly ...

Genesis10 is currently seeking a Lead Data Scientist - Remote for a direct hire opportunity with a Global Security and Risk Management Firm. Salary: $150,000 annually As a Lead Data Scientist in the ...

AI and Data Science Engineer III

Minneapolis, MN · On-site +1

$119K - $143K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

Data Scientist 1

Eden Prairie, MN · Remote

$60K - $107K/yr

This experience can include previous work in data science teams, business intelligence, financial reporting or analytics environments. * 1 years of experience in leveraging machine learning ...

MS or PhD in Statistics, Applied Mathematics, Computer Science, or other quantitative fields * 2+ years of experience with geospatial data (ex. GPS traces, spatial indexing systems, or routing ...

Sr. Data Scientist

Shakopee, MN · On-site +1

$106K - $152K/yr

Bachelor\'s Degree in Mathematics, Computer Science, Statistics, Data Science, or related field and ... Location: This role supports on-site, hybrid, or remote work based on geographic location.

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Showing results 1-20

Remote Data Science information

See Minnesota salary details

$22.8K

$101.6K

$193.8K

How much do remote data science jobs pay per year?

As of Jun 21, 2026, the average yearly pay for remote data science in Minnesota is $101,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,467.00 and $140,884.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Minnesota? The most popular types of Data Science jobs in Minnesota are:
What are popular job titles related to Remote Data Science jobs in Minnesota? For Remote Data Science jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Minnesota look for? The top searched job categories for Remote Data Science jobs in Minnesota are:
What cities in Minnesota are hiring for Remote Data Science jobs? Cities in Minnesota with the most Remote Data Science job openings:
Principal Data Scientist - Remote

Principal Data Scientist - Remote

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

Full-time

Retirement

Posted 13 days ago


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 141 frontline employees who took The Breakroom Quiz

187th of 874 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 Principal Data Scientist will play a pivotal role in supporting our Women's Health portfolio, leading advanced analytics initiatives and statistical analyses to demonstrate the clinical and economic value of our women's health products. The successful candidate will leverage expertise in data science, healthcare economics, and longitudinal health tracking to identify areas of opportunity that drive additional financial and clinical outcomes for women and infants across their health journeys (including reproductive health, maternity, menopause and etc.). This position is critical to ensuring our products deliver improved health equity, enhanced outcomes, and measurable financial impact within the US healthcare system.


You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.


Primary Responsibilities:

  • Value Demonstration: Lead and execute advanced statistical analyses and modeling to quantify and communicate the clinical and economic value of our women's health products to clients, payers, and strategic partners
  • Advanced Modeling: Apply advanced machine learning and causal inference techniques to complex, longitudinal healthcare datasets, optimizing methodologies to uncover robust, actionable insights into women's health outcomes
  • Cross-Functional Collaboration: Collaborate with cross-functional stakeholders, including women's health product managers, actuarial teams, clinical experts, and external customers, to translate product engagement and health outcomes into affordability projections and strategic roadmaps
  • Healthcare Economics: Design, implement, and validate health economics and outcomes models, such as cost-effectiveness and Return on Investment (ROI) frameworks, specifically tailored to women's health interventions (e.g., maternity management, fertility support, and neonatal health)
  • Data Pipelines: Develop and maintain reproducible analytics pipelines using statistical programming languages such as Python, R, or SAS, integrating diverse data sources from Snowflake and SQL databases
  • Strategic Communication: Communicate complex findings, predictive insights, and value metrics in a clear, compelling manner to both technical and non-technical audiences, including enterprise clients and clinical advisory boards
  • Data Stewardship: Champion best practices in data science, data integrity, and strict compliance with relevant healthcare data standards (e.g., HIPAA), ensuring ethical AI practices concerning sensitive demographic and reproductive health data


Positions in this function produce innovative solutions driven by exploratory data analysis from unstructured, diverse datasets typically measured in gigabytes or larger. Applies knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Uses a flexible, analytical approach to design, develop, and evaluate predictive and prescriptive models and advanced algorithms that lead to optimal value extraction from the data. Works with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data. This function is not intended for employees performing the following work: less complex analysis on small data sets; rules-based algorithmic or descriptive analytics; development of big data infrastructure.

  • Company thought leader
  • Functional SME
  • Broad business approach
  • Resource to senior leadership
  • Develops pioneering approaches to emerging industry trends


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:

  • Undergraduate degree in applicable area of expertise or equivalent experience
  • Master's or PhD degree in Data Science, Statistics, Mathematics, Health Economics, Econometrics, Epidemiology or a related discipline
  • 8 years of professional experience in data science or advanced analytics
  • Hands-on experience with Snowflake and SQL for large-scale data extraction, manipulation, and analysis
  • Thorough understanding of the US healthcare system, including payer/provider dynamics, healthcare economics, and value measurement frameworks
  • Demonstrated proficiency in statistical programming languages (e.g. SAS, R or Python)
  • Proven track record of applying advanced machine learning techniques in healthcare analytics to solve real-world business problems
  • Proven solid analytical, problem-solving, and communication skills, with the ability to convey complex concepts to diverse audiences


Preferred Qualifications:

  • Experience in leading multidisciplinary teams
  • Expertise in designing and validating novel healthcare economics models
  • Familiarity with cloud-based data platforms and scalable analytics architectures
  • Demonstrated ability to influence strategic decision-making through data-driven insights
  • Demonstrated exceptional stakeholder management and collaboration skills


*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy


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 $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.


Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.


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.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.


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


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