A leading organization is seeking a mid-level Data Scientist to support a high-visibility initiative focused on applying advanced artificial intelligence to complex healthcare data. This role centers on building an AI-driven utilization management criteria analyzer that helps business stakeholders understand the clinical and financial impact of changing medication utilization strategies.
The Data Scientist will work closely with technical and non-technical partners to design, develop, and evaluate large language model solutions, agent-based AI workflows, and data science models. The position combines hands-on development with direct stakeholder engagement and requires comfort operating in a fast-moving, evolving environment.
Responsibilities
Data science and modeling
- Perform exploratory data analysis, statistical analysis, and feature engineering on large, complex healthcare datasets.
- Develop and deploy scalable machine learning models to support forecasting, simulation, and decision intelligence use cases.
- Work with both structured and unstructured data, including clinical notes and claims data.
- Support scenario modeling and “what-if” analysis to quantify the impact of different utilization management strategies.
LLM and AI development
- Build large language model pipelines to extract metrics, values, units, and contextual information from unstructured clinical data.
- Design and refine prompt engineering strategies to improve consistency, accuracy, and reliability of LLM outputs.
- Develop explainable AI solutions that include supporting evidence and traceable reasoning.
- Evaluate model outputs for accuracy, hallucination risk, and overall performance, and drive iterative improvements.
Agentic AI systems
- Design and implement agent-based AI workflows that support multi-step reasoning and decision logic.
- Implement guardrails such as confidence scoring, validation checks, and fallback mechanisms.
- Orchestrate AI components to support complex analytical workflows and simulations.
Collaboration and platform development
- Partner with product, underwriting, and clinical strategy stakeholders to translate business problems into data science solutions.
- Contribute to the development of a self-service analytics and decision intelligence platform.
- Communicate insights clearly to business audiences and support stakeholder decision-making.
Required experience and skills
Core data science
- Strong proficiency in Python and SQL.
- Experience working with large datasets.
- Hands-on experience with exploratory data analysis, statistical analysis, and machine learning model development.
- Ability to analyze data and present findings to non-technical stakeholders.
LLM and AI
- Hands-on experience working with large language models.
- Demonstrated experience with prompt engineering and LLM evaluation frameworks.
- Experience building production-level LLM solutions.
Agentic AI
- Experience designing multi-step AI workflows.
- Familiarity with AI agents or orchestration logic.
- Experience implementing guardrails such as confidence scoring, validation, or fallback logic.
Data handling
- Experience working with unstructured data such as text, documents, or clinical notes.
- Strong skills in data extraction, transformation, and preparation.
Nice-to-have experience
- Experience in the healthcare or payer domain.
- Exposure to clinical data or chart data review workflows.
- Experience with forecasting, financial modeling, or scenario simulation systems.
- Familiarity with explainable AI approaches.
- Experience building recommendation systems.
This role requires strong communication skills, the ability to work directly with stakeholders, and the flexibility to adapt priorities as project needs evolve.