Counterpart Health is transforming healthcare by supporting primary care physicians with Counterpart Assistant to improve patient outcomes and reduce costs through early diagnosis and longitudinal care management of chronic conditions. The Data Science team leverages data to generate meaningful value, building models that assist physicians and identifying members who need specialized care. As a Senior Data Scientist, you will lead large-scale projects from ideation to enterprise impact, apply a broad problem-solving toolkit, evaluate trade-offs between out-of-the-box and customized solutions, and implement scalable, bug-free, and well-tested solutions that reduce complexity. You will understand business challenges, deliver results that address key problems, engage with stakeholders at all levels to align data science efforts with business needs, identify risks early, and mentor peers to improve team problem-solving and technical execution. Success in the first 90 days includes forecasting project impact and leading data-driven product performance assessments; beyond 90 days you will drive strategic improvements with data-driven strategies and contribute to better team outcomes. Requirements include an advanced degree in a quantitative field (Master's with 3-4 years or PhD with 2+ years), strong foundation in probability, statistics, and ML tools (SQL, Python, and relevant packages), and a track record of using data science to drive enterprise value. You should be able to lead projects from concept to measurable business impact and clearly communicate how your work supports

Counterpart Health is transforming healthcare by supporting primary care physicians with Counterpart Assistant to improve patient outcomes and reduce costs through early diagnosis and longitudinal care management of chronic conditions. The Data Science team leverages data to generate meaningful value, building models that assist physicians and identifying members who need specialized care. As a Senior Data Scientist, you will lead large-scale projects from ideation to enterprise impact, apply a broad problem-solving toolkit, evaluate trade-offs between out-of-the-box and customized solutions, and implement scalable, bug-free, and well-tested solutions that reduce complexity. You will understand business challenges, deliver results that address key problems, engage with stakeholders at all levels to align data science efforts with business needs, identify risks early, and mentor peers to improve team problem-solving and technical execution. Success in the first 90 days includes forecasting project impact and leading data-driven product performance assessments; beyond 90 days you will drive strategic improvements with data-driven strategies and contribute to better team outcomes. Requirements include an advanced degree in a quantitative field (Master's with 3-4 years or PhD with 2+ years), strong foundation in probability, statistics, and ML tools (SQL, Python, and relevant packages), and a track record of using data science to drive enterprise value. You should be able to lead projects from concept to measurable business impact and clearly communicate how your work supports