Data Science Engineer

Summary: Owns complex, cross-cutting statistical/ML and generative AI initiatives that solve high-impact clinical and business problems, setting technical direction for the area, mentoring data scientists, and partnering directly with clinical and business leaders.

Required Education & Experience

• Bachelor's degree (or higher) in a STEM field, or equivalent experience. • 6–9 years of experience in data science, with significant project ownership. • 4–6 years hands-on building and productionizing ML/generative AI solutions. • 4–6 years hands-on experience with R, RStudio, and Shiny application development, including production-grade interactive tools. • 1+ year informally mentoring data scientists.

Preferred

• Deep experience with responsible-AI evaluation in a pediatric/clinical setting. • Experience with fine-tuning or advanced RAG/agentic architectures. • Experience running analyses in an HPC or research-computing environment for large-scale or computing intensive studies. • Established working relationships with Research PIs, including study-design or analysis-planning input.

Knowledge, Skills, and Abilities

• Advanced expertise in statistics, ML, and data mining; independently designs model architectures and evaluation frameworks. • Advanced expertise in R and RStudio; independently designs and architects production-grade Shiny applications. • Deep understanding of generative AI/LLM architecture; independently designs RAG/agentic solutions for high-stakes…