Senior Data Scientist
Location: San Francisco, CA

About Waymark

Waymark is a mission-driven team of healthcare providers, technologists, and builders working to transform care for people with Medicaid benefits. We partner with communities to deliver technology-enabled, human-centered support that helps patients stay healthy and thrive. We’re designing tools and systems that bring care directly to those who need it most—removing barriers and reimagining what’s possible in Medicaid healthcare delivery.

Key Responsibilities

• Lead development and deployment of AI/ML models in clinical workflows for healthcare decision-making, patient targeting, and clinical intervention optimization.
• Duties include: design machine learning prediction models and LLM-based tools including multi-agent scheduling systems.
• Create technical documentation, system architecture, and project specifications.
• Collaborate cross-functionally with product, engineering, and care teams to define goals and timelines.
• Build and optimize Python-based data pipelines for claims data and CRM systems.
• Conduct research on healthcare data structures and predictive modeling techniques for publication in peer-reviewed journals.
• Manage multiple projects independently and supervise junior data scientists, providing technical leadership and mentorship. Telecommuting available. Multiple positions.

Minimum Qualifications

• Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a closely related quantitative field and one (1) year of experience in a data science or machine learning role, which may include industry experience, internships, or research assistantships, performing the following duties:
• Programming in Python for data processing and machine learning development, using pandas, NumPy, and scikit-learn;
• Writing SQL queries to extract, transform, and analyze data from relational or structured datasets;
• Working with tabular or event-driven datasets, including data cleaning, normalization, and schema alignment;
• Implementing automated data processing and model training pipelines, including feature engineering and data transformation;
• Developing and evaluating machine learning models using performance metrics and validation techniques;
• Supporting transition of machine learning models from development to production, including packaging, automation, or model versioning; and
• Using Git for version control in a collaborative development environment.

Salary Range:

$133,952 to $202,000 USD