• Engaging with sales leads as a “human explicability layer,” up-leveling understanding for non-technical audiences to ensure that complex underwriting results are communicated clearly to drive sales. • Leading complex and dynamic collaborations between the Data Science and Growth teams. • Helping us refine the competitiveness of our value-based care contracts. • Ensuring quality and availability of various data sources. • Leveraging a deep understanding of ML concepts (e.g., using SHAP or feature importance but also less formal quantitative instinct) to consult on the application of payment models. • Designing and engineering analytics tooling to stress-test our underwriting outputs. • Deepening knowledge of healthcare models. • Evaluating vendors and technologies.