Data Scientist IV – Medicare, ACA, Risk Adjustment

Data Scientist IV – Medicare, ACA, Risk Adjustment

Remote from any KP location in CA, OR, CO, WA, GA, MD, VA, HI or D.C. Only.

NOTE: Salary ranges are geographically based. The posted range reflects the Northern CA region. Lower salary ranges will apply for other labor markets outside of NCAL.

The Prospective Risk Adjustment Operations team is seeking a Data Scientist to support scoping, deploying, and reporting on projects to support prospective risk adjustment projects. This pivotal role will support the development of foundational reporting and analytical frameworks, identify and prioritize prospective risk initiatives, develop comprehensive reporting and insightful visualizations, and directly support strategic decision‑making and operational excellence. Ideal candidates will possess robust analytical skills and a proven ability to translate complex data into actionable business intelligence within a dynamic healthcare environment.

This individual contributor is primarily responsible for designing and developing data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and formats by transforming, cleansing, and storing data for consumption. This role is also responsible for developing detailed problem statements outlining hypotheses and their effect on target clients/customers, analyzing and investigating complex data sets and summarizing key characteristics, selecting, manipulating and transforming data into features used in machine learning algorithms, training statistical models, deploying and maintaining reliable and efficient models through production, verifying model performance, and collaborating with internal and external stakeholders across domains to develop and deliver statistically driven outcomes.

• Promotes learning by proactively providing and developing information, resources, advice, and expertise with coworkers and members; builds relationships with cross‑functional/external stakeholders and customers. Provides actionable feedback to others and managers, takes initiative for self‑development, and leads by influencing others through technical explanations and examples.
• Completes work assignments autonomously and supports business‑specific projects by applying expertise and business knowledge to generate creative solutions; encourages team members to follow processes and policies; collaborates cross‑functionally to achieve effective business decisions and resolve complex problems.
• Develops detailed problem statements outlining hypotheses and their effect on target clients/customers by defining scope, objectives, outcome statements and metrics.
• Designs and develops data pipelines and automation for data acquisition and ingestion from multiple data sources and formats, transforms, cleanses, and stores data for downstream processes; writes and optimizes SQL queries.
• Analyzes and investigates complex data sets, summarizes key characteristics using data visualization methods; determines how to manipulate data to discover patterns, spot anomalies, test hypotheses, and check assumptions.
• Selects, manipulates, and transforms data into features used in machine learning algorithms, employing dimensionality reduction, feature importance and feature selection techniques.
• Trains statistical models using various algorithms and data mining techniques; tests models with cross‑validation and techniques to prevent overfitting.
• Deploys and maintains reliable and efficient models through production.
• Verifies model performance using validation techniques, discriminating goodness of fit, and leveraging feedback to strengthen performance.
• Collaborates with internal and external stakeholders across domains to develop and deliver statistically driven outcomes, present findings to technical and non‑technical audiences, and support informed decision‑making.

Mid‑Senior level

Full‑time