Senior Full-Stack Data Scientist

Build the analytical foundation for a fast-growing, profitable health-tech company, where your data products and exploratory insights directly uncover breakdowns in drug access, helping millions of insured Americans receive the medications their benefits promise.

We are hiring a Senior Full-Stack Data Scientist to operate as a high-agency, autonomous individual contributor (IC). This role is a blend of entrepreneurial data exploration (30%) and building internal data applications (70%) that empower our business teams to make rapid, high-stakes decisions.

Unlike roles with rigid, pre-mapped pipelines, you will enter a highly ambiguous "zero-to-one" environment. You will field open-ended business questions, dig into messy data, determine where statistical concepts or machine learning can uniquely move the needle, and build the internal tooling to bring those solutions to life.

• Build Internal Data Products (70%): design, develop, and maintain internal data applications and web tools (e.g., using Streamlit, Dash, or custom frameworks) that leverage data and statistical concepts to automate decision-making for business teams.

• Exploratory Analytics & Prototyping (30%): attack highly open-ended, ambiguous business challenges. Investigate unstructured data to figure out what to build, prototyping machine learning or advanced statistical solutions where viable.

• Serve as a strategic data partner to leadership, rapidly fielding ad-hoc requests to uncover hidden gaps in benefit usage or drug affordability programs.

• Take complex, unmapped healthcare and financial data signals and translate them into a concrete data science roadmap.

• Work closely with product, operations, and analytics teams to turn messy backend data into clear, intuitive, and actionable business levers.

• 4–7 years of experience as a Full-Stack Data Scientist.

• Hands-on track record of building internal web tools, interactive dashboards, or data applications (Streamlit, Dash, Shiny, FastAPI/Flask, or similar).

• Mastery of SQL and Python (Pandas, NumPy, scikit-learn) to independently query, clean, and transform massive, unstructured datasets.

• Ability to operate independently with minimal direction. You are comfortable when there is no pre-defined roadmap and enjoy defining the problem as much as solving it.

• Strong foundational statistics to build reliable decision-making tools without over-engineering complex models where simple, elegant heuristics or trends work better.

• Experience with gradient boosting frameworks (XGBoost / LightGBM) for exploratory predictive modeling.

• Familiarity with U.S. healthcare-adjacent data structures (insurance claims, benefits, copay programs, or utilization metrics).

• Experience navigating compliance-aware or data-secure environments (HIPAA boundaries).

• You are not expected to build production-scale ML deployment infrastructure or manage containerized model pipelines.

• This is a dedicated, high-impact senior individual contributor role.

• Our client deals with the financial and operational mechanics of healthcare access, not molecular biology.

Build the analytical foundation for a fast-growing, profitable health-tech company, where your data products and exploratory insights directly uncover breakdowns in drug access, helping millions of insured Americans receive the medications their benefits promise.

We are hiring a Senior Full-Stack Data Scientist to operate as a high-agency, autonomous individual contributor (IC). This role is a blend of entrepreneurial data exploration (30%) and building internal data applications (70%) that empower our business teams to make rapid, high-stakes decisions.

Unlike roles with rigid, pre-mapped pipelines, you will enter a highly ambiguous "zero-to-one" environment. You will field open-ended business questions, dig into messy data, determine where statistical concepts or machine learning can uniquely move the needle, and build the internal tooling to bring those solutions to life.

• Build Internal Data Products (70%): design, develop, and maintain internal data applications and web tools (e.g., using Streamlit, Dash, or custom frameworks) that leverage data and statistical concepts to automate decision-making for business teams.

• Exploratory Analytics & Prototyping (30%): attack highly open-ended, ambiguous business challenges. Investigate unstructured data to figure out what to build, prototyping machine learning or advanced statistical solutions where viable.

• Serve as a strategic data partner to leadership, rapidly fielding ad-hoc requests to uncover hidden gaps in benefit usage or drug affordability programs.

• Take complex, unmapped healthcare and financial data signals and translate them into a concrete data science roadmap.

• Work closely with product, operations, and analytics teams to turn messy backend data into clear, intuitive, and actionable business levers.

• 4–7 years of experience as a Full-Stack Data Scientist.

• Hands-on track record of building internal web tools, interactive dashboards, or data applications (Streamlit, Dash, Shiny, FastAPI/Flask, or similar).

• Mastery of SQL and Python (Pandas, NumPy, scikit-learn) to independently query, clean, and transform massive, unstructured datasets.

• Ability to operate independently with minimal direction. You are comfortable when there is no pre-defined roadmap and enjoy defining the problem as much as solving it.

• Strong foundational statistics to build reliable decision-making tools without over-engineering complex models where simple, elegant heuristics or trends work better.

• Experience with gradient boosting frameworks (XGBoost / LightGBM) for exploratory predictive modeling.

• Familiarity with U.S. healthcare-adjacent data structures (insurance claims, benefits, copay programs, or utilization metrics).

• Experience navigating compliance-aware or data-secure environments (HIPAA boundaries).

• You are not expected to build production-scale ML deployment infrastructure or manage containerized model pipelines.

• This is a dedicated, high-impact senior individual contributor role.

• Our client deals with the financial and operational mechanics of healthcare access, not molecular biology.