Senior Data Scientist

Back to jobsSenior Data ScientistSan FranciscoApplyAbout Knit Health Knit Health is building a novel clinical foundation model to improve the way healthcare is delivered. We combine expertise in AI with deep clinical knowledge to develop safe, trustworthy systems that improve care, expand access, and reduce waste. Knit is led by a founding team from the University of California Berkeley who have developed a novel AI architecture which learns to reason like physicians. We’re now closing the loop and using our novel foundation model, together with frontier clinical LLMs, to build a next generation clinical intelligence platform for providers. We are venture backed and have partnered with multiple US-based health systems and data providers.Why this role Knit Health is seeking an experienced and visionary Senior Data Scientist to help advance our next-generation clinical intelligence platform at a pivotal time in healthcare innovation. We now have an unprecedented window into how clinicians make decisions at the point of care—and your work will turn that information into actionable insights that improve outcomes for patients and providers alike. As a senior member of our growing data science team, you will lead the design, curation, and analysis of complex, multi-system healthcare datasets—including EHR and claims data—powering our clinical foundation model. You’ll also guide model evaluation and methodology, mentor junior data scientists, and collaborate closely with AI engineering and product teams in a dynamic, fast-paced environment.  What you’ll do  Data Strategy, Analysis & Management Frame, design, execute and interpret ML-based data analyses in response to specific healthcare use cases.  Curate, clean, and integrate clinical datasets from multiple health systems to ensure high-quality inputs for model training and evaluation. Partner with Data Engineering on the design and implementation of large-scale data processing pipelines using structured and unstructured data (EHR, claims, medical text, ECG, etc.). Develop and maintain scalable data infrastructure, including database schemas and batch processing pipelines (e.g., Spark). Oversee data governance, quality control, and documentation to ensure reproducibility and compliance. Clinical Evaluation & Modeling Develop and refine evaluation frameworks that assess how models capture and represent clinical reasoning. Translate model outputs into clinically meaningful insights and metrics for diverse audiences.Collaborate with AI engineering to optimize models for performance, scalability, and real-world clinical relevance. Leadership & Collaboration Manage and mentor junior data scientists, fostering technical growth and best practices in modeling and analytics. Partner with product and engineering teams to align data science goals with product strategy and customer needs. Communicate complex technical concepts clearly to clinicians, stakeholders, and non-technical partners. Minimum qualifications Bachelor’s or Master’s degree in a quantitative field (e.g., mathematics, computer science, data science, statistics, or related discipline). 3–7 years of experience in data science, analytics, or machine learning. Demonstrated experience working with EHR data from multiple health systems and healthcare claims data. Proficiency in Python, SQL, and R. Hands-on experience with batch processing (e.g., Spark) and distributed data processing frameworks. Strong understanding of distributed database management systems and data warehouses (e.g., Snowflake, Redshift, BigQuery). Experience with machine learning methods, including deep learning, and associated pipelines (e.g., TensorFlow, PyTorch). Strong communication skills with the ability to translate complex analyses into actionable insights for diverse audiences. Proven track record of mentoring or managing junior team members. Nice-to-haves Experience developing evaluation frameworks for AI/ML models in healthcare. Familiarity...