Top Healthtech Data Science Jobs

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.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

The Senior Data Scientist leads data-driven initiatives, optimizing analytics for business decisions, mentoring staff, and ensuring data quality across healthcare projects.

Own the member-facing mobile (and near-term signed-in web) product roadmap for AI-powered genomic experiences. Drive activation, engagement, retention, and trust by translating intelligence-layer capabilities into polished consumer UX, rapid prototypes, experiments, and clear PRDs while partnering with AI platform, engineering, bioinformatics, design, and customer success.

Contribute to data pipelines, validate and refine analytical models, perform advanced analyses and data quality checks, collaborate with cross-functional teams, and write maintainable analytical code and documentation to support business decision-making.

Lead data science for Internal Audit by designing statistical and NLP models, building analytics frameworks and automated pipelines, creating monitoring dashboards, collaborating with audit teams, mentoring junior analysts, and presenting actionable findings to leadership to identify risks and improve controls.

Lead end-to-end clinical outcomes research using large EHR datasets: design observational and quasi-experimental studies, run causal inference analyses, interpret results, publish findings, and partner with clinicians, data science, and commercial teams to shape product and demonstrate impact.

The Data Scientist will analyze complex datasets, develop predictive models, and collaborate with stakeholders to drive data-driven decisions.

Lead research and development of longitudinal health trajectory models and next-best-action decision algorithms. Translate member data into deployable, clinically meaningful models, set evaluation standards, mentor scientists, and collaborate with product, engineering, and clinical teams to productionize and monitor ML solutions that optimize interventions and health outcomes.

Lead high‑impact data science initiatives across Global Operations, building production‑grade analytics, models, and dashboards (primarily in R), using Snowflake and Posit platforms, applying advanced statistics, ML, and LLM techniques, mentoring junior staff, and presenting insights to senior leadership to reduce supply chain risk and optimize manufacturing.