About this roleAt Waymark, our data science work is grounded in a specific and meaningful challenge: using claims, EHR, and care worker data to help community health workers, social workers, pharmacists, and care coordinators deliver better care to Medicaid patients.
As a Data Scientist you will contribute to building the models and tools that these care teams rely on - risk models, care gap prediction, and ML/AI applications including LLM-based tools that translate raw clinical data into actionable guidance. You will work closely with senior data scientists and engineers to learn how ideas move from prototype to production, and will be expected to take on increasing ownership as you develop in the role.
This is a position for someone who is technically strong, eager to learn healthcare data, and motivated by the idea that their work will directly affect the care of low-income patients.
Key Responsibilities- Build and validate ML and AI models on claims and EHR data for care delivery use cases including risk stratification and care gap identification, under guidance of senior data scientists
- Support the development of LLM-based tools and AI applications for care team workflows
- Develop and maintain Python code for data processing, model development, and ML pipelines, following software engineering best practices including version control, code review, and testing
- Collaborate with engineering, product, and analytics teams to understand requirements and translate them to technical solutions
- Develop Healthcare Subject Matter Expertise: Show a strong interest in healthcare data structures, quantitative methods, and data science applications in healthcare
Minimum Qualifications:- A Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Python Proficiency: 3+ years of hands-on Python experience including academic and project work - demonstrated through a GitHub portfolio or equivalent
- Solid foundations in statistical and machine learning methods, including classical ML and an understanding of modern AI and LLM applications
- Strong SQL skills and comfort working with large, messy real-world datasets
- Experience working with Git and collaborating in a team codebase
- Strong communication skills and ability to work closely with cross-functional stakeholders
Preferred Qualifications:- 1-2 years of industry data science experience
- Exposure to healthcare data (claims or EHR) through coursework, research, or work experience
- Familiarity with ML experimentation practices - experiment tracking, model validation, reproducible workflows
- Genuine curiosity about healthcare and its intersection with technology
Hiring RangeUS Employees in San Francisco/Bay Area, New York City - $123,000 - $164,000
US Employees in Boston, Los Angeles, Seattle, Washington DC - $113,000 - $151,000
US Employees in Arlington, Denver, San Diego, Sacramento - $108,000 - $144,000
US Employees in Albany, Atlanta, Austin, Baltimore, Central/Southern, Charlotte, Chicago, Dallas/Fort Worth, Detroit, Houston, Las Vegas, Miami, Milwaukee, Philadelphia, Portland, Research Triangle, Salt Lake City, Twin Cities - $98,000 - $131,000
US Employees in Baton Rouge, Birmingham, Charleston, Cincinnati, Cleveland, Daytona Beach, Indianapolis, Nashville, New Orleans, Omaha, Phoenix, Pittsburgh, St. Louis, Tampa - $95,000 - $127,000
In addition to salary, we offer a comprehensive benefits package. Here's what you can expect:Stock Options: Opportunity to invest in the company's growth.
Work-from-Home Stipend: A dedicated stipend for your first year to help set up your home office.
Medical, Vision, and Dental Coverage: Comprehensive plans to keep you and your family healthy.
Life Insurance: Basic life insurance to give you peace of mind.
Paid Time Off: 20 vacation days, accrued over the year, plus 11 paid holidays.
Parental Leave: 16 weeks of paid leave for birthing parents after six months of employment, and 8 weeks of bonding leave for non-birthing parents.
Retirement Savings: Access to a 401(k) plan with a company contribution, subject to a vesting schedule.
Commuter Benefits: Convenient options to support your commute needs.
Professional Development Stipend: A dedicated stipend supports professional development and growth.
