• Act as the cross functional owner of all aspects of Data Products including product development, partnerships, operations, and go-to-market • Establish Tap as the leading source for secondary trading insights for institutional investors and secondaries funds • Partner with LPs, GPs, and data vendors to acquire relevant private fund data over time • Create and maintain models behind valuation estimates, indices, and other Data Products • Iterate with clients, product, design, and engineering to incorporate Data Products into the broader Tap platform • Generate periodic reports and topical research utilizing Data Products • Drive adoption and awareness of Tap by syndicating Data Products into news publications, portfolio management systems, service providers, and other third parties • Devise and structure new data-driven transaction modalities like instant transactions or synthetic trading • Contribute to the big picture of company strategy and vision

• Support risk adjustment and quality initiatives for Value-Based Care programs across Medicare Advantage, ACA health plans, and Medicaid • Build and maintain risk-adjustment analytic modeling (HCC suspecting, recapture models, RAF forecasting) • Apply NLP and GenAI to medical records and clinical notes to extract structured clinical evidence • Develop LLM-assisted and agentic workflows to support medical record coding review, evidence summarization, and improved productivity and accuracy • Perform forecasting and scenario analysis tied to operational capacity and financial impact • Monitor model performance, bias, drift, and documentation sufficiency • Ensure analytics are explainable, auditable, and compliant • Partner closely with Product, Engineering, Coding, Clinical, Compliance, and Operations teams • Translate analytics into actionable signals embedded in payer workflows

• Own the planning, execution, and delivery of all data management activities across the study lifecycle. • Build and manage data management timelines, resourcing plans, and budgets; ensure on-time, on-scope delivery. • Act as the primary interface between Data Management, Clinical Ops, Biostats, Safety, and external vendors. • Proactively identify data risks, manage issues, and drive mitigation and escalation. • Ensure data quality standards are met and key milestones (interim locks, DBL) are achieved. • Provide clear status reporting, metrics, and decision support to study leadership.

• Design, build, and deploy machine learning models for real-time fraud detection and risk scoring. • Automate the monitoring of fraud and risk metrics using AI-driven alert systems. • Develop automated agents and systems to investigate and respond to suspicious activity, minimizing manual intervention. • Lead the research and implementation of cutting-edge AI and machine learning techniques for fraud prevention. • Conduct deep analysis of complex fraud patterns using advanced statistical and machine learning techniques. • Collaborate with engineering and product teams to integrate fraud prevention logic directly into our products. • Continuously optimize our models and detection strategies based on performance data. • Own the development and reporting of KPIs that measure the effectiveness of our AI-based fraud systems.