Principal Data Scientist
About The Position
The Principal Data Scientist is the singular technical authority for data science within the 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 (LLMs) 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. It owns 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 data scientists, serves as the principal technical reviewer for important team work, and contributes to AI governance and model monitoring. The position is listed as hybrid, with regular in-office attendance required to support collaboration and business needs. It is a regular, full-time position on the day shift, Monday through Friday, with weekend work as needed. The schedule is 40 hours per week. The annual pay range is $181,896.00 to $291,033.60, with the applicable range potentially varying by work location. Eligible positions include a comprehensive benefits package.
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 required degree or diploma.
- 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 supervised, unsupervised, and deep learning techniques.
- Mastery of LLM and generative AI techniques, including evaluation, fine-tuning, retrieval-augmented generation, prompt engineering, and agent development.
- Advanced knowledge of Python and SQL.
- Knowledge of applicable regulatory and risk frameworks, including HIPAA, FDA SaMD guidance, and NIST AI RMF, and of bias and fairness evaluation.
- Strong written and verbal communication skills, including the ability to explain complex technical work to executive and clinical audiences.
- Demonstrated ability to mentor technical staff and influence without authority.
Nice To Haves
- Knowledge of Epic EHR 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.
- Engage with clinical, operational, and information systems stakeholders to understand and frame problems.
- Own analytical and data science 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 authority.
- Serve as the principal technical reviewer for the team’s most important work.
- Contribute to AI governance and model monitoring.
- Translate complex technical work for executive and clinical audiences.
Benefits
- Eligible positions include a comprehensive benefits package.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
