Senior Data Scientist

Why this role

The data science team is responsible for understanding provider needs and clinical workflows, then turning patient-level clinical data from EHRs and Knit’s clinical models into scientifically sound solutions that can be used in healthcare settings.

This role matters because model performance alone is not enough. The solutions must reflect how clinical data is actually generated through care delivery, fit into complex provider workflows, address meaningful operational needs, and produce insights that clinicians and healthcare organizations can use.

As a senior member of a small data science team, this person will also help establish strong scientific and analytical practices while supporting the growth of junior team members.

What you’ll do

You’ll own complex clinical problems from discovery through deployment: working with provider partners and clinicians to understand care workflows, extracting and shaping patient-level EHR data, designing scientifically sound solutions using Knit’s data and models, and evaluating and deploying tools that can be used in real healthcare settings.

Clinical Data & Scientific Analysis

• Work directly with patient-level EHR data to understand clinical events, care pathways, and how care delivery is represented in the underlying data.
• Extract, curate, clean, and integrate longitudinal clinical datasets from multiple health systems, turning messy real-world data into reliable inputs for analysis, modeling, and deployed applications.
• Design and execute analyses that answer important questions about clinical data, model performance, and healthcare outcomes.
• Develop reproducible methodologies for preparing, interpreting, and validating datasets used across the organization.
• Work closely with clinicians and provider partners to ensure analyses and solutions accurately reflect clinical context and real-world care delivery.

Model Evaluation

• Develop evaluation frameworks that measure how well models capture clinically meaningful reasoning and decision patterns.
• Design experiments that help improve model quality, robustness, and real-world usefulness.
• Translate model outputs into insights that are meaningful for both technical and clinical audiences.

Data Infrastructure

• Partner with Data Engineering to build scalable processing pipelines across structured and unstructured healthcare data (EHR, claims, medical text, ECG, etc.).
• Improve data quality, governance, reproducibility, and documentation.
• Help shape scalable infrastructure supporting model development.

Collaboration & Leadership

• Mentor and support junior data scientists through technical guidance and best practices.
• Partner closely with engineering, product, and clinical teams to prioritize work and solve complex problems.
• Help establish strong scientific and analytical practices as our team grows.

Minimum Qualifications

• 4+ years of experience in data science, analytics, or machine learning.
• Demonstrated experience working directly with patient-level EHR data, including an understanding of the clinical workflows and care processes that generate it, and experience extracting, transforming, analyzing, or modeling that data.
• Experience partnering directly with clinicians, physicians, or provider organizations to translate clinical problems into analytical or machine learning solutions.
• Experience building or owning data products, models, or analytical tools that were deployed into real-world clinical or operational workflows.
• Strong proficiency in Python and SQL, with experience applying machine learning methods, including deep learning, and working with modern ML frameworks such as PyTorch or TensorFlow.
• Strong communication skills with the ability to translate complex analyses into actionable insights for diverse audiences.
• Proven track record of leading complex analytical or technical projects; experience mentoring other data scientists is preferred.

Nice-to-Haves

• Experience working at an early-stage startup or in a fast-moving, ambiguous environment.
• Experience developing evaluation frameworks for AI/ML models in healthcare.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and their data engineering services.
• Experience applying natural language processing (NLP) to clinical or medical text.

You'll join a small, highly collaborative team where data scientists work directly with AI engineers, clinicians, and company leadership. This is an opportunity to help define how clinical foundation models are evaluated and deployed in real healthcare settings, with meaningful ownership over both technical direction and product impact from an early stage.

Salary Range

Knit Health offers a competitive compensation package that includes base salary, equity, and opportunities for advancement. The starting salary range for the Senior Data Scientist is approximately $140,000 to $175,000 per year.