Principal Data Scientist; Remote

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.

Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

You’ll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges.

Build Credit Models:

• Develop and maintain predictive models for application and behavioral scoring, probability of default (PD), loss given default (LGD), and early risk detection, ideally for commercial line of credit products
• Design models for underwriting, fraud detection, credit line management, and collections strategies

Feature Engineering & Data Innovation:

• Create advanced features using alternative data sources (e.g., bank transaction data, health care claims data, cash flow, open banking, etc.)
• Evaluate new data vendors and enrich internal datasets to improve model performance

End-to-End Ownership:

• Take models from prototype to production in partnership with Data Engineering and Product teams
• Build interpretable and compliant models aligned with FCRA, ECOA, and fair lending standards

Performance Monitoring & Iteration:

• Own model monitoring, validation, reporting and back testing, regularly recalibrating for shifts in macroeconomic conditions or borrower behavior

Collaborate Cross-Functionally:

• Work with Risk, Product, Compliance and Finance teams to integrate model outputs into strategy
• Communicate insights clearly to technical and non-technical stakeholders

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.

• Master’s degree in a quantitative discipline (Statistics, Mathematics, Data Science, Economics, Computer Science, etc.)
• 5+ years experience working with Python or R and SQL; familiarity with cloud environments like AWS, GCP, or Snowflake
• 5+ years of experience working with lending lifecycle and credit risk KPIs (e.g., delinquency, charge-offs, approval rates, ROI, CAC/payback)
• 4+ years of experience in credit risk modeling, ideally at a fintech, neobank, or consumer lending startup for commercial line of credit products
• 4+ years of experience with both traditional statistical techniques (e.g., logistic regression, scorecards) and modern machine learning

• Experience with real-time underwriting or decisioning APIs
• Work in embedded finance, BNPL, gig economy lending, or small business credit
• Familiarity with explainability frameworks (e.g., SHAP, LIME)
• Exposure to model governance or regulatory reviews
• Comfort working in a dynamic, test-and-learn environment with incomplete data
• Proven solid communication skills and attention to model transparency, fairness, and compliance

* All employees working remotely will be required to adhere to United Health 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…