Senior Data Scientist, Health Risk Analytics

Kaiser Permanente; Oakland (CA); On-site; USD 166,000 - 215,000; Full time

Job summary

Kaiser Permanente is seeking a Data Scientist IV in the Risk Adjustment Analytics team in Oakland, CA. You will design end-to-end data science solutions to improve risk score accuracy across Medicare Advantage, ACA, and Medicaid programs using Python and cloud analytics.

You will develop data pipelines, build features for ML models, and deploy production models while collaborating with clinical, actuarial, and operations teams to extract actionable insights for executives.

Qualifications

• 3+ years of Exploratory Data Analysis (EDA) and visualization.
• 3+ years of machine learning and/or algorithmic experience.
• 3+ years of statistical analysis and modeling experience.
• 3+ years of programming experience.
• 1+ year of leadership experience (with/without direct reports).
• Bachelor’s degree in a relevant field with 5+ years in data science or equivalent work experience; advanced degrees may substitute.

Responsibilities

• Designs and develops data pipelines for ingestion and storage of multi-source data.
• Transforms and cleans data, builds features for ML models, and deploys production models.
• Explains hypotheses and outcomes to technical and non‑technical stakeholders.
• Collaborates across clinical, actuarial, and operations teams to drive data-driven decisions.
• Mentors junior data scientists and promotes a data-driven culture.

Skills

EDA & visualization

ML & modeling

Python

Data pipelines

Leadership

Education

Bachelor's degree in Mathematics, Statistics, CS, Engineering, Economics, Public Health, or related field

Advanced degree may substitute for work experience

Tools

Python

SQL

Kubernetes

Docker

Cloud platforms

Job description

Kaiser Permanente is seeking a Data Scientist IV in the Risk Adjustment Analytics team in Oakland, CA. You will design end-to-end data science solutions to improve risk score accuracy across Medicare Advantage, ACA, and Medicaid programs using Python and cloud analytics.

You will develop data pipelines, build features for ML models, and deploy production models while collaborating with clinical, actuarial, and operations teams to extract actionable insights for executives.