What you\'ll doData 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 with cloud platforms (AWS, GCP, or Azure) and their data engineering services.
- Knowledge of natural language processing (NLP) for medical text corpuses.
- Prior work in a startup or high-growth environment.
Salary RangeKnit 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.
BenefitsGenerous benefits for full-time employees include: medical, dental, and vision coverage with 100% of premiums paid for employees and dependents (full coverage for dental, vision, and our Gold medical plan; employees may choose to buy up to Platinum); coverage begins on the first day of employment. Additional benefits include a 401(k) plan and 24 days of PTO annually.
Final NotesPlease note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
