Senior Data Scientist

Prominence Advisors is actively seeking a Senior Data Scientist to join our team.

Who We Are

Prominence is a healthcare and life sciences technology and consulting firm dedicated to helping leading organizations do more with their data. With deep expertise across the full ecosystem — spanning providers, payers, and life sciences — we turn complex data into actionable insight. We deliver a full spectrum of services, including advisory, analytics, optimization, and IT staffing. Our work helps organizations operate more efficiently, improve patient outcomes, and deliver measurable financial impact through smarter use of data. Recognized as a 2x Best in KLAS organization, we partner with more than 120 health systems and 40 life sciences organizations, including 7 of the top 10 U.S. News & World Report-ranked institutions. Through our life sciences brands, Tegra Analytics and WLH Consulting & Learning Solutions, we extend these capabilities to pharmaceutical and biotech organizations — combining data, consulting, and learning to advance commercial excellence. By connecting strategy, data, and execution, we help organizations translate data into clarity, strategy into action, and vision into measurable results. At our core, we are a people-first, values-driven organization that believes strong teams and trusted partnerships are what ultimately make healthcare and life sciences smarter.

Job Summary

Prominence is looking for a Senior Data Scientist with deep experience in applied machine learning, statistical modeling, and generative AI to help deliver advanced analytics solutions alongside some of the nation's leading healthcare providers. This role will design, build, and deploy models and AI-powered applications that help healthcare organizations improve patient outcomes, optimize operations, and accelerate research. Helping our customers harness the power of generative AI by building LLM-powered applications that unlock new possibilities for clinical and operational workflows.

Design, build, validate, and deploy machine learning models across the full data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, and monitoring.

Develop advanced analytics solutions for clinical prediction, population health, operational optimization, and research enablement.

Build AI-powered applications leveraging LLM APIs, prompt engineering, and RAG pipelines to support clinical and operational workflows.

Ability to work with diverse healthcare data sources including EHRs, claims, and clinical registries.

Translate complex analytical findings into meaningful, actionable insights for clinical and operational stakeholders.

Manage documentation of best practices and scalable frameworks that can be applied across client engagements.

Mentor and guide client counterparts to build the skills needed to sustain and expand on project deliverables.