Principal Data Scientist - Strategic Insights

UnitedHealth Group•Eden Prairie, MN

2h•$112,700 - $193,200•Hybrid

About The Position

UnitedHealth Group is seeking a Principal Data Scientist for its Strategic Insights team. Reporting to the Director of Data Science, this senior individual contributor will shape and advance enterprise-level analytics connecting customer experience, brand, and business performance. The role develops scalable analytical frameworks aligned with the Enterprise Performance Management (EPM) system to measure leading indicators, experience metrics, and business outcomes across key value chains. It applies advanced statistical and AI-driven approaches to identify performance drivers, quantify impact across quartiles, and turn complex data into actionable insights for executive decision-making. The role operates with substantial autonomy and influences senior leaders and cross-functional stakeholders to support customer-centric strategies, growth, and long-term value creation. The position leads connected analytics across experience measures such as NPS and CAHPS, brand perception, and business performance; develops reusable and standardized analytical methods; integrates experience, brand, market, and operational data; and supports experimentation with AI-enabled approaches. It also evaluates vendor and internal capabilities, tests proof-of-concept solutions, promotes responsible and interpretable AI practices, and identifies opportunities to automate and scale recurring analytics workflows. The role offers hybrid-remote flexibility for people living near Eden Prairie, Minnesota. Telecommuters must adhere to UnitedHealth Group’s Telecommuter Policy. The role is eligible for bonuses based on sales performance. The posting lists an hourly pay range of $112,700 to $193,200 based on full-time employment.

Requirements

At least 8 years of experience in data science, advanced analytics, or applied statistical modeling.
At least 8 years of experience with quantitative methods such as regression, segmentation, predictive modeling, and multivariate analysis.
Experience developing analytical frameworks, reusable methodologies, or standardized approaches that improve scalability and consistency.
Experience applying AI/ML techniques to business problems, including experimentation with synthetic data, simulation, or AI-assisted analytics workflows.
Advanced proficiency with Microsoft Suite, including Excel and PowerPoint.
Proficiency with tools such as Python, SQL, or R, and experience with data visualization and reporting tools.
Demonstrated ability to work with large, complex datasets and integrate multiple data sources for advanced analytics.
Demonstrated ability to simplify complex data into actionable insights and compelling, executive-ready narratives.
Strong problem-solving skills and ability to navigate ambiguity and structure analytical approaches.
Ability to build and strengthen relationships across teams and functions to drive alignment, collaboration, and business impact.
Effective communication skills, including explaining technical concepts to non-technical audiences.
Experience working across teams and functions to solve complex business problems and influence decision-making.

Nice To Haves

Experience in customer experience, market research, or insights analytics, such as NPS, CAHPS, or brand measurement.
Experience evaluating or working with external data science or AI vendors, tools, or platforms.
Familiarity with integrating analytics into broader business strategies, including growth, retention, and customer experience optimization.
Healthcare industry experience.

Responsibilities

Lead enterprise analytics connecting customer experience (including NPS and CAHPS), brand perception, and business performance across the EPM system.
Apply and guide advanced statistical and analytical methods, such as regression, segmentation, predictive modeling, and correlation analysis, to identify drivers, relationships, and trends.
Translate complex analytical results into clear narratives that influence business decisions and promote data-driven insights.
Develop and standardize analytical frameworks, approaches, and reusable methodologies to improve consistency, scalability, and quality.
Integrate experience measurement, brand, market, and operational data to enable connected analytics and a holistic view of customer and business performance.
Support AI-driven approaches, including synthetic data, simulation, and AI-assisted analytics, to improve the depth, speed, and flexibility of insights generation.
Partner with and evaluate external vendors and internal stakeholders on AI-enabled capabilities, tools, and data science solutions for business alignment and research rigor.
Lead experiments and proof-of-concept work to test AI-driven analytical approaches and assess business value using a build, validate, and scale approach.
Develop and promote best practices for integrating AI into analytics workflows while ensuring outputs are interpretable, reliable, and aligned with research and governance standards.
Identify opportunities to embed automation, standardization, and AI-assisted processes into recurring workflows.