Overview:
Kaiser Permanente’s Northern California (NCAL) Regional Pharmacy Operations is seeking a Data Scientist IV, Biostatistics to support a diverse range of pharmacy service domains, including ambulatory care, inpatient, outpatient, oncology, and supply chain. This role leverages Kaiser Permanente’s broad longitudinal data to drive meaningful improvements in service delivery and patient outcomes.
You will partner with various teams to assess populations and outcomes, evaluate workflows, extract actionable insights, recommend and implement improvements, and establish sustainable monitoring systems. You’ll function as both a data expert and a solutions architect, helping teams build robust infrastructure for their services, while contributing to a collaborative analytics team and engaging with broader communities of practice that value shared learning, data storytelling, and methodological rigor.
The role involves applying advanced analytical methods such as causal inference, outcomes/cost analyses, benchmarking, health equity assessments, predictive modeling, reinforcement learning, and large language models. You will also support a variety of pharmacy residency research projects annually by providing study design consultation and data support. The position offers various opportunities for professional development, creative exploration, collaboration, and contributions to publications.
This role requires deep expertise in data science, biostatistics, study design, SQL, Python or R, and data visualization tools such as Tableau or Power BI. Ideal candidates will have real-world experience leading end-to-end projects in health research and advanced analytics. The position is primarily remote, with occasional in-person meetings in Pleasanton, CA.
Job Summary:
In addition to the responsibilities listed below, this senior individual contributor biostatistician is also responsible for contributing to the research process by actively leading sections of grant proposals and scientific publications; developing documentation to capture the processes and project workflows as they relate to data management and statistical methods; setting metrics to ensure data quality; and translating statistical and algorithmic models to aid in the drawing of conclusions about study populations.
Essential Responsibilities:
Promotes learning in others by proactively providing and/or developing information, resources, advice, and expertise with coworkers and members; builds relationships with cross-functional/external stakeholders and customers. Listens to, seeks, and addresses performance feedback; proactively provides actionable feedback to others and to managers. Pursues self-development; creates and executes plans to capitalize on strengths and develop weaknesses; leads by influencing others through technical explanations and examples and provides options and recommendations. Adopts new responsibilities; adapts to and learns from change, challenges, and feedback; demonstrates flexibility in approaches to work; champions change and helps others adapt to new tasks and processes. Facilitates team collaboration to support a business outcome.
Completes work assignments autonomously and supports business-specific projects by applying expertise in subject area and business knowledge to generate creative solutions; encourages team members to adapt to and follow all procedures and policies. Collaborates cross-functionally and/or externally to achieve effective business decisions; provides recommendations and solves complex problems; escalates high-priority issues or risks, as appropriate; monitors progress and results. Supports the development of work plans to meet business priorities and deadlines; identifies resources to accomplish priorities and deadlines. Identifies, speaks up, and capitalizes on improvement opportunities across teams; uses influence to guide others and engages stakeholders to achieve appropriate solutions.
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 of raw data from multiple data sources and data formats by transforming, cleansing, and storing data for consumption by downstream processes; writing and optimizing diverse SQL queries; and demonstrating advanced knowledge of database fundamentals.
Analyzes and investigates complex data sets and summarizes key characteristics by employing data visualization methods; and determining how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and/or check assumptions.
Selects, manipulates, and transforms data into features used in machine learning algorithms by leveraging techniques to conduct dimensionality reduction, feature importance, and feature selection.
Trains statistical models by using algorithms and data mining techniques; testing models with various algorithms to assess the input dataset and related features; and applying techniques to prevent overfitting such as cross-validation.
Deploys and maintains reliable and efficient models through production.
Verifies model performance by demonstrating expertise in the practice of a variety of model validation techniques to assess and discriminate the goodness of model fit; and leveraging feedback and output to manage and strengthen model performance.
Collaborates with internal and external stakeholders across domains to develop and deliver statistical driven outcomes by delivering insights and values from heterogeneous data to investigate complex problems for multiple use cases; driving informed decision-making; and presenting findings to both technical and non-technical audiences.
Minimum Qualifications:
Minimum three (3) years medical or health analytics experience.
Minimum three (3) years statistical modeling experience using SAS, R, or another advanced statistical package.
Masters degree in Biostatistics, Statistics, Public Health, Data Science, or related field OR Minimum five (5) years medical or health analytics experience.
Minimum three (3) years experience working with Exploratory Data Analysis (EDA) and visualization methods.
Minimum three (3) years machine learning and/or algorithmic experience.
Minimum three (3) years statistical analysis and modeling experience.
Minimum three (3) years programming experience.
Minimum one (1) year experience in a leadership role with or without direct reports.
Bachelors degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or related field AND Minimum five (5) years experience in data science or a directly related field. Additional equivalent work experience in a directly related field may be substituted for the degree requirement. Advanced degrees may be substituted for the work experience requirements.
Additional Requirements:
Knowledge, Skills, and Abilities (KSAs): Health Care Coding; Internal or External Publication; Procedure Manuals and Documentation; Process Mapping; Advanced Quantitative Data Modeling; Algorithms; Applied Data Analysis; Data Extraction; Data Visualization Tools; Machine Learning; Relational Database Management; Microsoft Excel; Design Thinking; Business Intelligence Tools; Data Manipulation/Wrangling; Data Ensemble Techniques; Feature Analysis/Engineering; Open Source Languages & Tools; Model Optimization; Strategic Thinking; Deep Learning/Neural Networks; Project Management
COMPANY: KAISER
TITLE: Data Scientist IV, Biostatistics
LOCATION: Oakland, California
REQNUMBER: 1361847
External hires must pass a background check/drug screen. Qualified applicants with arrest and/or conviction records will be considered for employment in a manner consistent with Federal, state and local laws, including but not limited to the San Francisco Fair Chance Ordinance. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, protected veteran, or disability status.