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.
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.