Top Healthtech Data Science Jobs

Own and evaluate national and subnational projection models using large-scale healthcare claims. Build evaluation studies, diagnostic tooling, and benchmarks. Investigate customer-raised anomalies, communicate methodology, review model code with engineering, and maintain documentation to ensure model quality and trust.

As a Trainee Data Scientist, you'll assist in data cleaning, model development, exploratory analysis, and presenting insights to stakeholders.

Build data filtering and curation pipelines for VLM and classifier training sets, develop model-based data-quality signals, design clinical evaluation methodology for radiology report generation, maintain clinical benchmarks, validate model-based evaluators against radiologist judgment, and implement continuous evaluation and regression testing across the research stack.

Design and deliver AI-powered analytics, dashboards, and decision-support tools for commercial healthcare teams. Build LLM-based agents, use cloud data platforms (Azure/AWS/Snowflake), ensure data governance and compliance, translate complex healthcare data into executive-ready insights, and automate insight generation to support growth and operations.

The Data Scientist II will oversee data management, design study protocols, train staff, lead report development, and manage client activities using project frameworks.

The Research Intern will assist in data curation, exploratory analysis, and implementation of machine learning models in healthcare applications.

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.