About the job
Join Prominence Advisors as a Senior Data Scientist and be part of a team that is transforming healthcare through innovative data-driven solutions.
About Us
At Prominence Advisors, we are dedicated to helping healthcare and life sciences organizations leverage their data for impactful change. Our expertise spans the entire ecosystem , covering providers, payers, and life sciences , enabling us to turn complex data sets into actionable insights that improve patient outcomes and operational efficiency.
We pride ourselves on offering a comprehensive range of services, including advisory, analytics, optimization, and IT staffing. Our partnerships with over 120 health systems and 40 life sciences organizations, including seven of the top-ranked institutions in the U. S. News & World Report, demonstrate our commitment to excellence. Recognized as a two-time Best in KLAS organization, we help our clients achieve measurable financial results through smarter data utilization.
Through our specialized life sciences brands, Tegra Analytics and WLH Consulting & Learning Solutions, we extend our capabilities to pharmaceutical and biotech sectors, combining data, consulting, and education to drive commercial excellence.
By integrating strategy, data, and execution, we empower organizations to turn data into clarity, strategy into action, and vision into measurable outcomes. We are a people-first, values-driven firm that believes in the power of strong teams and trustworthy partnerships to enhance healthcare and life sciences.
Position Overview
We are in search of a Senior Data Scientist with extensive experience in applied machine learning, statistical modeling, and generative AI. In this role, you will design, build, and deploy predictive models and AI-powered applications that enhance patient outcomes, streamline operations, and expedite research initiatives. Your work will involve harnessing the capabilities of generative AI to create LLM-powered applications that unlock new potential in clinical and operational workflows.
- Lead the design, development, validation, and deployment of machine learning models throughout the data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, and ongoing monitoring.
- Create advanced analytical solutions for clinical predictions, population health management, operational efficiencies, and research facilitation.
- Develop AI-driven applications utilizing LLM APIs, prompt engineering, and Retrieval-Augmented Generation (RAG) pipelines to enhance clinical and operational processes.
- Collaborate with diverse healthcare data sources, including Electronic Health Records (EHRs), claims data, and clinical registries.
- Translate intricate analytical findings into clear, actionable insights for clinical and operational stakeholders.
- Document best practices and scalable frameworks for application across client engagements.
