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Remote Causal Inference Jobs in Minnesota (NOW HIRING)

Remote Causal Inference information

What is a remote causal inference?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

What are the key skills and qualifications needed to thrive as a remote causal inference specialist?

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote causal inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.

What are the most commonly searched types of Causal Inference jobs in Minnesota?

The most popular types of Causal Inference jobs in Minnesota are:

What are popular job titles related to Remote Causal Inference jobs in Minnesota?

For Remote Causal Inference jobs in Minnesota, the most frequently searched job titles are:

What cities in Minnesota are hiring for Remote Causal Inference jobs?

Cities in Minnesota with the most Remote Causal Inference job openings:

Infographic showing various Remote Causal Inference job openings in Minnesota as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Sr Principal Data Scientist - Remote

Minnetonka, MN • On-site, Remote


UnitedHealth Group
Insurance Services • 10K+ employees

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

192nd of 896 rated healthcare providers

Good employer

Recommended by students

Recommended by parents


Full-time

Retirement

Posted 6 days ago


Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.


We are seeking a highly accomplished and innovative Senior Principal Data Scientist to provide technical and analytical leadership for a strategic enterprise program focused on transforming complex business processes through advanced analytics, Artificial Intelligence (AI), and Machine Learning (ML). In this role, you will serve as a senior technical authority and strategic thought partner, applying deep expertise in data science, AI/ML, statistical modeling, experimentation, and decision science to solve high-impact enterprise challenges. Operating in ambiguity, you will frame complex and undefined problems, define new analytical approaches, and translate complex data into actionable insights and scalable AI-driven solutions that generate measurable business value. You will also shape the organization's advanced analytics and AI capabilities by establishing analytical standards, advancing innovative methodologies (including Generative AI, Large Language Models, and agentic capabilities), and mentoring data science talent across the enterprise.


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:

  • Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI, collaborating across research, engineering, and product teams to translate cutting-edge AI advancements into scalable, reusable enterprise capabilities
  • Serve as a senior technical leader and subject matter expert for enterprise data science, advanced analytics, AI, and machine learning initiatives across multidisciplinary teams
  • Lead analytical strategy for highly complex enterprise challenges, analyzing large-scale datasets to uncover hidden patterns, emerging trends, anomalies, and previously unexploited business opportunities
  • Develop predictive, prescriptive, causal, optimization, and decision intelligence solutions, applying advanced statistical methods, machine learning, Generative AI, and agentic AI capabilities
  • Frame ambiguous business challenges into testable hypotheses, lead rigorous experimentation and model validation, and deliver executive-level recommendations that influence strategic decision-making
  • Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle
  • Use enterprise-approved AI tools to streamline workflows, automate tasks, evaluate emerging trends, and drive continuous improvement
  • Establish best practices for model development, explainability, monitoring, reproducibility, and responsible AI while mentoring data science talent across the organization


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:

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or another quantitative discipline, or equivalent experience (e.g., 4 additional years of quantitative analysis experience in lieu of degree)
  • 10 years of progressive experience in Data Science, Advanced Analytics, Machine Learning, AI, Operations Research, or related quantitative disciplines leading complex analytical initiatives
  • 5 years of experience with Python, R, SQL, or comparable programming languages for statistical modeling and data manipulation
  • 5 years of experience working with machine learning frameworks and ecosystems (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost)
  • 3 years of experience framing ambiguous business challenges, conducting hypothesis testing, experimental design, causal inference, and model validation on large-scale datasets
  • 3 years of experience providing technical leadership, mentoring data scientists, and establishing modeling standards
  • 3 years of experience translating technical analytics into executive-level narratives to influence business and investment decisions


Preferred Qualifications:  

  • Master's degree or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or related quantitative discipline
  • Advanced expertise applying Generative AI, Large Language Models (LLMs), Agentic AI, NLP, or emerging AI technologies to enterprise business problems
  • Experience architecting and operationalizing AI-enabled decision intelligence solutions, recommendation systems, anomaly detection, or forecasting systems at scale
  • Experience with cloud-based analytics and AI platforms (e.g., AWS, Azure, GCP) and modern enterprise data ecosystems
  • Experience establishing model governance, explainability, monitoring, and lifecycle management (MLOps) in complex or highly regulated enterprise environments
  • Demonstrated track record of developing reusable analytical platforms, frameworks, accelerators, or intellectual property across enterprise functions

*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 $134,600 - $230,800 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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