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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Principal Data Scientist - Remote - **Company:** UnitedHealthcare - **Location:** Minnetonka, MN, United States (Remote available) - **Experience:** Expert - **Salary:** $134,600.0 - $230,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Databases, Information Engineering, Data Visualization, Python (Programming Language), Machine Learning, Power BI, Tensorflow, SQL Databases, Tableau (Software), Google Cloud, Cloud Platform System, Pytorch, Scikit Learn, Information Technology, Optimization Algorithms, Data Analytics - **Published:** May 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eae679723442c3ff ## About the Role Do you have experience in Technical documentation?, Do you have a Bachelor's degree?, The position requires deep expertise in statistical modeling, machine learning, and data engineering principles, along with the ability to translate complex analytics into actionable business strategies. 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., * Analytical Rigor: Ability to solve complex problems with structured, data-driven approaches * Business Acumen: Strong understanding of how analytics drives financial and operational outcomes * Communication: Ability to simplify and present complex concepts clearly and effectively * Collaboration: Works effectively across cross-functional teams * Ownership & Accountability: Drives work from concept to execution with minimal oversight * Innovation Mindset: Continuously seeks opportunities to improve processes and outcome 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., * Bachelor's degree in MIS, Statistics, Mathematics, Computer Science * 6+ years of experience performing complex data analysis, report development, querying high volume data, and interpreting results * 6+ years proficiency in SQL, and data visualization tools (e.g., Tableau, Power BI) * 6+ years experience working with large, complex datasets (healthcare data preferred: claims, clinical, or population health datasets) * 2+ years of experience in creating relevant databases (tables/fields/libraries) needed to source appropriate data * 2+ years of experience building and executing data pulls using SQL and / or other BI reporting tools * 1+ years of experience with documenting processes and practices, often in accepted project methodology artifacts, * Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or related field * 4+ years exposure to cloud-based data platforms (Azure, AWS, GCP) * 3+ years experience with real-time or near-time analytics * 2+ years experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) * 2+ years experience in Python * Healthcare industry experience, particularly in population health, care management, product value sales story development and/or payer environments * All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy ## Description The Data Scientist is a senior-level individual contributor responsible for developing advanced analytics, predictive models, and data-driven insights that directly influence strategic business decisions. This role partners cross-functionally with clinical, product, operations, and client-facing teams to solve complex problems, optimize outcomes, and drive measurable value., Advanced Analytics & Modeling: * Design, develop, and deploy predictive and prescriptive models to support business and clinical initiatives * Apply machine learning, statistical analysis, and optimization techniques to large, complex datasets * Build and validate models for use cases such as risk stratification, utilization forecasting, intervention targeting, and cost containment * Ensure model performance, scalability, and ongoing monitoring * Guide analytics teams in applying machine learning, statistical modeling, and simulation techniques (e.g., regression, classification, clustering, ensemble methods) to large, multi-source datasets * Apply best practices in causal inference, AI/ML, quasi-experimental methods, and forecasting to support strategy decisions and benefit realization * Create and/or complete needed documentation to define project parameters and specifications, process flow and other business documentation including, but not limited to: business/functional/report/analytics requirements, workflows, job aids, and reference materials * Apply analytical, mathematical and statistical techniques to investigating and interpreting data results * Works with less structured, more complex issues, and comfortable with ambiguity Business & Strategic Impact: * Translate ambiguous business problems into structured analytical frameworks * Deliver actionable insights that inform product development, population health strategies, and client-specific solutions * Support cost-of-care initiatives, cross product benefits, and engagement strategies through analytics Stakeholder Collaboration: * Partner with operations, product managers, consultants, and reporting teams to align analytics with business needs * Communicate findings clearly to both technical and non-technical stakeholders, including executive leadership * Serve as a thought partner in client discussions, RFPs, and strategic initiatives Data Engineering & Governance: * Partner with data engineering teams to define data requirements, pipelines, and data quality standards * Ensure reproducibility, traceability, and governance of analytical outputs * Work with claims, clinical, and engagement data sources to enable integrated analytics Innovation & Continuous Improvement: * Identify opportunities to leverage emerging technologies (AI/ML, generative AI, advanced analytics platforms) * Drive enhancements in modeling approaches, tools, and analytical methodologies * Contribute to the development of reusable analytics assets and frameworks Scope & Impact: * Works on high-priority, enterprise-level initiatives * Influences product strategy, clinical outcomes, and client retention * Supports revenue growth, cost savings, and performance guarantees * Acts as a technical leader and mentor to junior analysts/data scientists (informal leadership) ## Related Videos - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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