Manager, Data Strategy & Analytics

Accountabilities

• Develop and maintain KPI frameworks covering enrollment, engagement, retention, acute care utilization, symptom burden, patient and provider experience, and AI safety.

• Produce recurring monthly and quarterly performance reports, executive presentations, board materials, and client-facing analyses.

• Conduct outcomes analyses using appropriate quantitative methods, including cohort comparisons, pre/post analyses, survival analysis, cost-avoidance modeling, survey analysis, and longitudinal symptom tracking.

• Partner with client success teams and external stakeholders to define success criteria, align methodologies and comparison cohorts, and establish effective reporting cadences.

• Participate in client meetings, business reviews, and joint operating committees by providing analytical insights, interpretation, and supporting materials.

• Build and maintain validated source-of-truth queries for critical metrics and develop scalable reporting workflows and self-service analytics capabilities.

• Collaborate with Data Engineering, Product, and Engineering teams across modern cloud and analytics environments, including Azure, Databricks, and Tableau.

• Manage analytics intake, prioritization, documentation, data quality, and lineage across production data environments.

• Develop ROI models, financial impact analyses, benchmarking frameworks, and proof-of-value materials to support prospective clients and commercial initiatives.

• Partner with Sales and Marketing to ensure external data claims are accurate, defensible, and supported by validated evidence.

• Support value-based care contracting discussions through analytics framing, measurement strategies, and evidence development.

• Lead analytics and reporting for AI performance monitoring and quality governance, including safety, accuracy, clinician review, and model performance metrics.

• Identify opportunities for predictive and prescriptive analytics in areas such as risk stratification, early intervention, resource allocation, and care pathway optimization.

• Evaluate emerging AI and large language model capabilities that could enhance analytics workflows, including automated insights and natural-language querying.

• Coordinate analytics priorities across Product, Engineering, Clinical Operations, Commercial, and external partners while providing structured updates and ad hoc analyses for leadership.

Requirements

• 5+ years of experience in healthcare analytics, health system strategy, population health, or a closely related discipline.

• Demonstrated experience managing complex analytics projects or workstreams involving multiple stakeholders and competing priorities.

• Proven ability to develop outcomes measurement frameworks and performance reporting for health systems, executives, clients, or senior leadership.

• Strong SQL expertise, including the ability to write, validate, troubleshoot, and maintain complex production queries against relational databases.

• Experience with enterprise business intelligence platforms; Tableau experience is strongly preferred.

• Working knowledge of healthcare economics, including fee-for-service and value-based reimbursement, payer contracting, acute care cost structures, and oncology payment models such as the Enhancing Oncology Model.

• Experience designing and interpreting quantitative research, including cohort studies, pre/post comparisons, survival analysis, and survey analysis.

• Ability to transform complex datasets and analytical findings into concise, actionable recommendations for nontechnical audiences.

• Strong communication, presentation, stakeholder management, and problem-solving skills, with the ability to work effectively across technical, clinical, commercial, and operational teams.

• Ability to work independently, manage multiple priorities, and adapt effectively within a growth-stage environment.

• Experience in oncology care delivery or cancer center operations is preferred.

• Familiarity with healthcare data monetization, real-world evidence generation, or partnerships with pharmaceutical and life sciences organizations is a plus.

• Knowledge of AI/ML monitoring, LLM evaluation, quality governance, or clinical decision-support safety frameworks is advantageous.

• Experience with Databricks, cloud data platforms, or modern analytics engineering workflows is preferred.

• Experience developing ROI models, financial impact analyses, or value-based contracting analytics for health system or payer audiences is beneficial.

• Exposure to predictive or prescriptive healthcare analytics, including risk stratification, intervention targeting, or resource optimization, is a plus.

• Candidates must be located within the United States.

Benefits

• Remote work opportunity within the United States.

• Opportunity to work at the intersection of healthcare analytics, virtual care, AI, and value-based care.

• High-impact role with exposure to client, executive, commercial, clinical, and technology stakeholders.

• Opportunity to contribute to outcomes measurement, AI quality governance, commercial analytics, and emerging healthcare data initiatives.

• Broad cross-functional exposure across Product, Engineering, Clinical Operations, Commercial, and Analytics teams.

• Opportunity to develop scalable analytics infrastructure and influence how data supports strategic decision-making.

• Potential for the role to be leveled at Director based on experience, with expanded strategic, client-facing, and functional leadership responsibilities.

• Additional compensation and benefits are subject to the partner company's applicable employment package.