Top Healthtech Data Science Jobs

The Advanced Data Science Manager leads a team of data scientists, develops data science strategies, manages client projects, and drives business development while providing thought leadership and mentoring.

The Principal Data Scientist will design and implement advanced AI/ML systems, lead development of large-scale machine learning solutions, and drive AI innovation in healthcare while mentoring other data scientists.

As a Data Science Intern, you will develop and validate LLM pipelines for extracting clinical endpoints from EHR data, ensuring data quality for clinical analysis.

Apply data science and operations research methods to analyze large, unstructured datasets, build statistical models and optimization algorithms, generate insights, and communicate findings to leadership. Develop processes, tools, and evaluations for complex problems using Python, visualization, and version control.

Partner with product, engineering, design, ops, and clinical teams to define metrics and experiments. Design and analyze A/B tests and quasi-experiments, apply causal inference when needed, perform funnel/cohort analyses, build and validate predictive models, and operationalize insights with monitoring and launch criteria. Produce clear, decision-ready analyses and raise organizational standards for metrics and experimentation.

The Senior Data Scientist will design and implement AI-enabled products using clinical trial data, mentor team members, and collaborate with stakeholders.

As a Senior Applied AI Data Scientist, you will leverage machine learning to transform clinical data into high-quality research datasets and collaborate with stakeholders on model validation and insights generation.

The Data Scientist II will lead RWE studies, derive insights from real-world clinical data, and contribute to methodologies using advanced statistical techniques and AI tools, collaborating closely with pharmaceutical partners.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.