Top Healthtech Data Science Jobs

Leads projects in data science to analyze complex data sets using advanced statistical methods, providing insights for business decisions and managing cross-functional teams.

Senior data leader accountable for Vibrant's enterprise data strategy, unifying analytics, data science, ML, and AI. Owns governance, BI platform architecture, ML/AI model development and responsible AI frameworks, budgeting, compliance, and team building to deliver predictive models, dashboards, and equitable reporting for programs and executive stakeholders.

Lead development and operationalization of data-driven financial forecasting (time-series, AI/ML, causal, Monte Carlo). Integrate statistical outputs into Anaplan planning, establish model governance/validation, build templates/dashboards, collaborate with FP&A and Data/IT, and create a Center of Excellence for advanced forecasting and repeatable playbooks.

Lead strategy and execution for Growth Analytics by building executive scorecards, financial and workforce planning, and organizational programs. Own vision, roadmap, delivery, adoption, and impact measurement for AI- and analytics-driven data products while partnering with data teams and stakeholders to drive data-driven decisions and measurable business outcomes.

Design, validate, and deploy predictive models using claims, clinical, pharmacy, and lab data to improve population health, utilization management, and care quality. Partner with clinical and business teams, evaluate model performance, scale analytical approaches, and communicate insights to technical and non-technical stakeholders.

Lead identification and delivery of high-impact data science solutions from concept to production using advanced analytics, machine learning, and deep learning. Collaborate with cross-functional stakeholders, prototype proofs-of-concept, and communicate insights to drive business decisions across Roche Diagnostics.

Use real-time and historical healthcare data to prepare, clean, analyze, and visualize metrics and dashboards (Tableau). Extract data via SQL, interpret results, share insights and recommendations with internal and external stakeholders, respond to ad-hoc analytics requests, and ensure deliverable quality through peer review.

Work with product, engineering, and data teams to generate, label, and evaluate medication-focused datasets, review AI outputs for clinical accuracy, provide SME guidance for product features, ensure safety/compliance, and improve clinical intelligence processes and tooling.

Drive causal and machine learning analyses to measure product feature impacts, develop KPIs, and create visualizations while collaborating with cross-functional teams.

Lead a data science team to deliver data-driven solutions in life sciences, applying machine learning, NLP, and AI methods. Oversee project management, stakeholder collaboration, and ensure high-quality standards in data science practices.