Data Scientist building and validating ML/AI models (including LLMs) on claims and EHR data to support care teams in delivering better Medicaid healthcare. Requires Master's, 3+ years Python, strong ML foundations, and SQL skills.
Salary not listed
Remote3+ YOEData Science
About the role
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
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