Senior Data Scientist - Clinical AI & EHR Analytics

Knit Health; San Francisco (CA); On-site; USD 140,000 - 175,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage (

401(k) plan

24 days PTO annually

Job summary

Knit Health in San Francisco is seeking a Senior Data Scientist to turn patient-level clinical data from EHRs into scientifically sound models and decision-support tools for providers.

You will work with clinicians, engineers, and product to design, deploy, and evaluate ML solutions, mentor junior teammates, and help shape data infrastructure, governance, and analytics practices across the company.

Qualifications

• 4+ years of data science, analytics, or ML experience.
• Experience working with patient-level EHR data and clinical workflows.
• Experience partnering with clinicians to translate problems into ML solutions.
• Experience deploying data products/models into real-world clinical workflows.
• Strong Python and SQL skills; experience with ML frameworks (PyTorch or TensorFlow).
• Excellent communication to translate analyses for diverse audiences.
• Leadership or mentoring experience preferred.

Responsibilities

• Own complex clinical problems from discovery to deployment with provider partners.
• Extract, curate, and model patient-level EHR data for analytics and deployed applications.
• Design experiments and evaluation frameworks for model quality and robustness.
• Collaborate with clinicians, engineers, and product teams to align analytical work with care workflows.
• Mentor and support junior data scientists; contribute to data infrastructure and governance.

Skills

Python

SQL

Machine learning

Deep learning

PyTorch

TensorFlow

Communication

Leadership

Mentoring

NLP (optional)

Tools

PyTorch

TensorFlow

Job description

Knit Health in San Francisco is seeking a Senior Data Scientist to turn patient-level clinical data from EHRs into scientifically sound models and decision-support tools for providers.

You will work with clinicians, engineers, and product to design, deploy, and evaluate ML solutions, mentor junior teammates, and help shape data infrastructure, governance, and analytics practices across the company.