Principal Data Scientist

Sutter Health•Sacramento, CA
•Hybrid

About The Position

The Principal Data Scientist is the singular technical authority for data science within Sutter Health’s Center for Applied Artificial Intelligence team. The role addresses the organization’s highest-impact problems through advanced statistical analysis, exploratory data analysis, and predictive model development, supplemented by large language models and other generative AI methods as needed. The position works directly with clinical, operational, and information systems stakeholders to understand problems and translate them into technical solutions, owning work end to end—from data acquisition and transformation through model development, validation, and production deployment. The role also sets technical direction and standards for the team, mentors fellow data scientists, serves as the principal technical reviewer for the team’s most important work, and contributes to AI governance and model monitoring. The position is listed as hybrid and requires regular in-office attendance. It is a regular, exempt, full-time position with a day shift schedule, Monday through Friday, and weekend work as needed.

Requirements

  • Bachelor’s degree in Statistics, Biostatistics, Computer Science, Mathematics, Data Science, Medical Informatics, or a related field; equivalent experience may be accepted in lieu of the degree.
  • 10 years of recent relevant experience.
  • Progressive experience in computer science, applied statistics, or machine learning.
  • Demonstrated track record of taking analytic work from stakeholder problem framing through production deployment with measurable impact.
  • Expert command of advanced statistical methods, including regression, time series, survival analysis, causal inference, and experimental design.
  • Expert command of machine learning techniques, including supervised learning, unsupervised learning, and deep learning.
  • Mastery of large language model and generative AI techniques, including evaluation, fine-tuning, retrieval-augmented generation, prompt engineering, and agent development.
  • Advanced knowledge of Python and Structured Query Language (SQL).
  • Knowledge of applicable regulatory and risk frameworks, including HIPAA, FDA Software as a Medical Device guidance, and the NIST AI Risk Management Framework, as well as bias and fairness evaluation.
  • Strong written and verbal communication skills, including the ability to translate complex technical work for executive and clinical audiences.
  • Demonstrated ability to mentor technical staff and influence without authority.

Nice To Haves

  • Knowledge of Epic Electronic Health Record data structures, including Clarity and Caboodle.
  • Knowledge of clinical data standards, including HL7 and FHIR.

Responsibilities

  • Solve high-impact organizational problems using advanced statistical analysis, exploratory data analysis, predictive modeling, and generative AI methods as needed.
  • Work directly with clinical, operational, and information systems stakeholders to understand and frame problems.
  • Own analytics and modeling work from data acquisition and transformation through model development, validation, and production deployment.
  • Set technical direction and standards for the data science team.
  • Mentor fellow data scientists and influence technical staff without formal authority.
  • Serve as the principal technical reviewer for the team’s most important work.
  • Contribute to AI governance and model monitoring.

Benefits

  • Eligible positions include a comprehensive benefits package.
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