Research Scientist Senior

This role requires associates to be in-office 1-2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. Ideal candidates will be able to report to one of our Pulse Point locations in Indianapolis, IN, Atlanta, GA, Grand Prairie, TX, Chicago, IL, or New York, NY. Alternate locations may be considered if candidates reside within a commuting distance from an office. Candidates not within a reasonable commuting distance will not be considered unless an accommodation is granted as required by law.

About the Role

The Research Scientist Senior is responsible for prospective and retrospective health economic research activities, leading the assessment of scientific research that contributes to the transformation of health outcomes research to achieve substantial national and global leadership. This role focuses on the design, development, evaluation, and deployment of advanced machine learning and reinforcement learning systems that optimize healthcare and operational decision-making.

Responsibilities

• Leads the assessment of scientific research to transform health outcomes research and achieve national/global leadership.
• Acts as a technical authority within the organization and nationally/globally.
• Publishes findings and conclusions in recognized scientific publications and presents research at scientific conferences and forums.
• Leads projects that generate project extensions.
• Leads research project operations, including project conceptualization, planning, team leadership, and proposal defense presentations.
• Leads the proposal development process, project pricing, and milestone forecasting.
• Ensures the quality and timeliness of deliverables to research clients.
• Serves as a hands-on individual contributor building scalable AI/ML solutions and production-grade decision intelligence systems in highly regulated healthcare environments.
• Develops scalable machine learning and reinforcement learning systems to improve healthcare outcomes, operational efficiency, and member experience through adaptive learning and advanced analytics.
• Demonstrates deep expertise in machine learning, reinforcement learning, predictive analytics, and intelligent decision systems.
• Applies strong research discipline and evidence-based methodologies to complex healthcare and operational problems.
• Delivers scalable machine learning solutions from concept through deployment and measurable operational impact.
• Partners effectively across business, research, engineering, analytics, and product teams.
• Evaluates emerging AI technologies and translates innovation into scalable business value.
• Communicates highly technical concepts effectively to both technical and non-technical audiences.
• Leads prospective and retrospective health economic and outcomes research initiatives using healthcare administrative datasets, including pharmacy and medical claims.
• Designs and develops machine learning, predictive modeling, and reinforcement learning solutions for healthcare optimization and intelligent decision systems.
• Builds and operationalizes production-grade ML systems.
• Partners closely with engineering, architecture, analytics, product, and business teams to deploy AI-driven recommendations and decision systems into operational workflows.

Requirements

Requires a PhD in health service research, biostatistics, epidemiology, health policy, economics, or a related field, or a clinical degree such as an MD or PharmD with residency or fellowship research training. A minimum of 10 years of increasing responsibility as a subject matter expert on research teams in health outcomes projects is required, with excellence demonstrated by extensive publication of articles and presentation of research at national and international conferences, and serving as a technical subject expert on health services research panels. Any combination of education and experience providing an equivalent background will be considered.

Preferred Skills

• Hands-on expertise with Python and modern ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or Ray.
• Experience building end-to-end machine learning systems and production AI infrastructure.
• Experience with reinforcement learning, predictive modeling, recommendation systems, or adaptive decision systems.
• Experience with cloud-native ML environments, distributed computing, and MLOps practices.
• Experience with healthcare AI, clinical decision support, or intelligent automation systems in regulated industries.
• Experience operationalizing Generative AI or LLM-enabled workflows.

Pay

For candidates working in Chicago, IL or New York, NY, the salary range for this position is $156,464 to $256,032.

Benefits

In addition to salary, Elevance Health offers a comprehensive benefits package, including:

• Incentive and recognition programs
• Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements)
• Medical, dental, and vision benefits
• Short and long-term disability benefits
• Paid holidays and Paid Time Off
• Life insurance
• Wellness programs and financial education resources

Schedule

Elevance Health operates in a Hybrid Workforce Strategy. Associates are required to work at an Elevance Health location at least once per week, and potentially several times per week. Specific requirements and expectations for time onsite will be discussed as part of the hiring process.