• Collaborate with scientists, engineers, and technical product owners to create technical solutions • Deliver production solutions for data extraction, classification, routing, search, and decision-making using foundation models • Manipulate and analyze data programmatically, derive statistically sound insights, and communicate findings that address technical and business considerations • Engineer and evaluate foundation model prompts systematically across domain datasets • Design comprehensive evaluation frameworks using precision, recall, F-1 scores, accuracy, and operational metrics • Own documentation and mentor junior team members through systematic problem-solving approaches • Decompose complex problems into measurable components, optimize across multiple dimensions, and articulate trade-offs

• Collaborate closely with your team and key stakeholders to convert business requirements into Machine Learning solutions. • Foster a culture that values data-driven decision-making within the organization and aid in the enhancement of our data platform. • Offer ML and engineering expertise and ensure your team builds, deploys and maintains high standards models. • Drive innovation and creativity within your team, encouraging them to explore new data science techniques and approaches. • Empower your team by supporting members to grow and take ownership of data science projects. • Cultivate and demonstrate an action-oriented approach, encouraging your team to experiment, iterate, drive initiatives forward, even amidst ambiguity and continually assess and improve the team's performance, setting clear expectations and providing constructive feedback.

• Support the firm’s business across both banking and markets regulatory regimes • Own capital, margin, liquidity, and counterparty risk analytics that shape product design, settlement structures, regulatory engagement, and growth strategy

• Utilize reference data sources and advanced validation techniques to ensure accuracy, completeness, and integrity of healthcare claims data • Assess provider scoring methodologies, identify discrepancies, and develop insights to optimize coverage accuracy • Design, develop, and maintain retrospective models for historical performance analysis, and predictive models to identify high-risk patients and prioritize actionable interventions • Translate complex analytical findings into clear, actionable insights, and effectively communicate results and recommendations to internal stakeholders and external clients • Aggregate and reconcile multiple data sources, applying statistical and computational methods to verify data integrity, identify anomalies, and implement necessary corrections • Execute comprehensive data analysis workflows, evaluate outcomes, and implement enhancements to improve model accuracy and data reliability • Review and optimize claim-matching processes, troubleshoot inconsistencies, and resolve data discrepancies to maintain high-quality outputs • Investigate data quality issues, conduct root cause analysis, document findings, and deliver actionable recommendations for process improvements • Collaborate with cross-functional teams to enhance analytical tools, refine methodologies, and implement scalable solutions that improve efficiency and analytical capabilities