Principal Data Scientist

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., Please Note: While this position is listed as hybrid, regular in-office attendance is required. Candidates should be prepared to commute to the office on a regualr basis to support team collaboration and business needs.*

Equivalent experience will 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 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 Epic Electronic Health Record (EHR) data structures (Clarity, Caboodle) and clinical data standards (Health Level Seven [HL7], Fast Healthcare Interoperability Resources [FHIR]) preferred.
• 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.

These Principal Accountabilities, Requirements and Qualifications are not exhaustive but are merely the most descriptive of the current job. Management reserves the right to revise the job description or require that other tasks be performed when the circumstances of the job change (for example, emergencies, staff changes, workload, or technical development).