Top Healthtech Data Science Jobs

As a Data Scientist, you will advance applied ML capabilities for healthcare, develop LLM-based chart abstraction techniques, and enhance data science best practices.

The Data Scientist supports AI-driven initiatives, conducts analytics, builds machine learning algorithms, and develops technical reports. They work with large datasets to drive business improvements and enhance patient lifetime value.

Provide analytics and data-driven insights for CoverMyMeds clients, prioritize work that drives commercial outcomes, build relationships with account teams, apply statistical and predictive methods, monitor portfolio health, deliver client-facing visuals and recommendations, support complex requests and escalations, and inform strategic decisions across product, analytics, and operations.

The Head of Data Science & AI Engineering leads Ipsen's technical strategy in advanced analytics and AI, overseeing data products, mentoring teams, and ensuring compliance in a dynamic biopharmaceutical environment.

The Senior Manager, AI and Data Science will lead the development of AI solutions, collaborate across functions, and implement machine learning models to support biomedical applications, focusing on healthcare data integration and operational efficiency.

Support AI, analytics, and data modernization for VA research: perform ETL, statistical programming, reporting, dashboards, LLM-enabled analytics, data integration, quality validation, and executive-level presentations to improve operational decision-making.

The Manager of Advanced Analytics will lead the design and implementation of data solutions, mentor team members, and collaborate with stakeholders to drive analytics strategy and improvements in patient outcomes.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Design and build petabyte-scale data pipelines and platform tooling to ingest, transform, catalog, and deliver heterogeneous biological datasets for AI research. Improve reliability, observability, and automation (agent-based curation/QA) while collaborating with AI researchers and scientists.