Principle Data Scientist - Remote

UnitedHealth Group•Eden Prairie, MN

2d•$112,700 - $193,200•Remote

About The Position

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. 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

Requirements

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

Nice To Haves

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

Responsibilities

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
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
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
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)
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
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
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