Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Principal Data Scientist role.
Rezi rewrites your resume against Sutter Health's job description. Free.
Tailor your resume to this Principal Data Scientist role.
Rezi rewrites your resume against Sutter Health's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Principal Data Scientist posting at Sutter Health — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Principal Data Scientist posting at Sutter Health — free, in seconds.
About the Role
The singular technical authority for data science within the center for applied artificial intelligence (AI) team. This role solves the organization's highest-impact problems primarily through advanced statistical analysis, exploratory data analysis, and predictive model development, supplemented by Large Language Models (LLMs) and other generative AI methods as needed. Engages directly with clinical, operational, and information systems (IS) stakeholders to understand the underlying problem, translates it into a technical solution, and owns the work end-to-end — from data acquisition and transformation through model development, validation, and production deployment. In parallel, the role 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.
Responsibilities
- Solves the organization's highest-impact problems primarily through advanced statistical analysis, exploratory data analysis, and predictive model development, supplemented by Large Language Models (LLMs) and other generative AI methods as needed.
- Engages directly with clinical, operational, and information systems (IS) stakeholders to understand the underlying problem, translates it into a technical solution, and owns the work end-to-end — from data acquisition and transformation through model development, validation, and production deployment.
- 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.
- Contributes to AI governance and model monitoring.
Requirements
- Equivalent experience will be accepted in lieu of the required degree or diploma.
- Bachelor's degree in Statistics, Biostatistics, Computer Science, Mathematics, Data Science, Medical Informatics, or related field required.
- 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 to production deployment with measurable impact.
- Expert command of advanced statistical methods (regression, time series, survival analysis, causal inference, experimental design) and machine learning techniques (supervised, unsupervised, deep learning).
- Mastery of with Large Language Model (LLM) and generative AI techniques (evaluation, fine-tuning, retrieval-augmented generation, prompt engineering, agent development).
- Advanced knowledge of Python and Structured Query Language (SQL).
- Knowledge of applicable regulatory and risk frameworks (Health Insurance Portability and Accountability Act [HIPAA], Food and Drug Administration [FDA] Software as a Medical Device [SaMD] guidance, National Institute of Standards and Technology Artificial Intelligence Risk Management Framework [NIST AI RMF]) and with bias and fairness evaluation.
- Strong written and verbal communication; able to translate complex technical work for executive and clinical audiences.
- Demonstrated ability to mentor technical staff and influence without authority.
Skills
- Computer science
- Applied statistics
- Machine learning
- Advanced statistical methods
- Regression
- Time series
- Survival analysis
- Causal inference
- Experimental design
- Supervised learning
- Unsupervised learning
- Deep learning
- Large Language Model (LLM)
- Generative AI techniques
- Evaluation
- Fine-tuning
- Retrieval-augmented generation
- Prompt engineering
- Agent development
- Python
- Structured Query Language (SQL)
- Epic Electronic Health Record (EHR) data structures (Clarity, Caboodle)
- Clinical data standards (Health Level Seven [HL7], Fast Healthcare Interoperability Resources [FHIR])
- Regulatory and risk frameworks
- Health Insurance Portability and Accountability Act (HIPAA)
- Food and Drug Administration (FDA) Software as a Medical Device (SaMD) guidance
- National Institute of Standards and Technology Artificial Intelligence Risk Management Framework (NIST AI RMF)
- Bias and fairness evaluation
- Written communication
- Verbal communication
Location
- Hybrid
Work Type
- Full Time
- Hybrid
Experience Level
- 10 years of recent relevant experience
Education Level
- Bachelor's degree in Statistics, Biostatistics, Computer Science, Mathematics, Data Science, Medical Informatics, or related field
Salary/Compensations
- $181,896.00 to $291,033.60 / annual salary
Benefits
- Yes
About the Company
- Sutter Health is an equal opportunity employer EOE/M/F/Disability/Veterans.
Equal Opportunity
- EOE/M/F/Disability/Veterans