Principal AI Data Scientist, E&I Affordability

UnitedHealth Group•Orlando, FL

1d•$112,700 - $193,200•Remote

About The Position

At UnitedHealthcare, we’re simplifying the health care experience, creating healthier communities and removing barriers to quality care. The work you do here impacts the lives of millions of people for the better. Come build the health care system of tomorrow, making it more responsive, affordable and optimized. Ready to make a difference? Join us to start Caring. Connecting. Growing together The E&I Affordability team is transforming how affordability opportunities are identified, prioritized, and executed through the use of artificial intelligence, advanced analytics, and automation. As a Principal Data Scientist, you will serve as a strategic leader responsible for developing AI-driven solutions that accelerate affordability outcomes at scale. This role will work across affordability, medical cost data/analytics, and technology teams to connect complex healthcare datasets, generate actionable insights, and build intelligent solutions that improve medical cost management. You will help shape the future of affordability by reducing the time required to identify opportunities, increasing the impact of interventions, and advancing enterprise AI capabilities. This aligns with broader E&I Affordability efforts to leverage AI-powered affordability engines, unified healthcare data assets, and intelligent workflow automation to drive medical cost savings and operational efficiencies. This is a unique opportunity to influence the future of affordability within UnitedHealthcare by developing innovative AI solutions that improve speed, scale, and impact. You'll work on highly visible initiatives, partner with enterprise leaders, and help redefine how affordability opportunities are discovered and executed across the organization. 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.

Requirements

7+ years of experience in data science, applied statistics, machine learning, or artificial intelligence
5+ years of SQL experience
4+ years of programming experience in Python and/or R
3+ years working with healthcare payer, provider, or health plan data
Hands-on experience with healthcare claims data (medical, pharmacy)
Demonstrated experience deploying models into production environments and measuring real-world impact on cost, quality, or outcomes
Experience mentoring data scientists and setting technical direction for a team
Proven excellent communication skills, with experience presenting to actuarial, clinical, and executive audiences
Willing and able to travel 10%25 +/- depending on business need

Nice To Haves

Experience with Snowflake or Databricks

Responsibilities

Lead large, complex Data Science and AI initiatives from problem framing through deployment, measurement, and value realization.
Translate ambiguous business challenges into scalable analytical, machine learning, causal inference, optimization, or AI-driven solutions
Design and build AI-enabled products, research agents, and analytical capabilities that connect enterprise data sources and generate actionable insights
Provide technical architecture and solution design guidance for analytical products and production AI systems
Establish best practices for feature engineering, model development, validation, evaluation, governance, and deployment
Conduct technical reviews and ensure analytical rigor, scalability, and business impact across initiatives
Partner with business, product, engineering, and technology leaders to identify opportunities, prioritize investments, and realize measurable value
Drive innovation through emerging AI technologies, reusable frameworks, intellectual property, and modernized analytical platforms
Develop intelligent workflow, portfolio management, and decision-support capabilities that improve execution efficiency and outcome tracking
Communicate insights, recommendations, and business value to executive leadership and influence strategic decision-making
Represent Data Science in enterprise architecture, governance, and technology strategy discussions
Lead cross-functional initiatives focused on affordability, cost management, operational efficiency, and business transformation