Data Scientist Analyst

Elevance Health•Louisville, IN

1d•Hybrid

About The Position

This role requires associates to be in-office 1 day per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Ideal candidates will be able to report to one of our Pulse Point locations in Indianapolis, IN, Louisville, KY or Waukesha, WI. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. As a Data Scientist Analyst, you will support the development of innovative analytics and AI solutions that uncover early signals in cost trends across Medicaid, Medicare, Local Group, and Individual markets. You’ll collaborate with actuaries, finance leaders, and business stakeholders to enhance decision-making through advanced modeling, automation, and insight delivery. In this role, you will help modernize how emerging cost drivers are detected using real-time data, AI-powered insights, and dynamic tools to support critical decisions for executive, actuarial, and financial audiences. Join us to shape the future of health cost forecasting.

Requirements

Requires a Bachelor’s degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines and 1 or more years of experience in predictive analytics or equivalent; or any combination of education and experience, which would provide an equivalent background.

Nice To Haves

Prior experience in healthcare analytics or trend analysis is a strong advantage highly preferred.
Proven ability to communicate technical findings and complex concepts to a non-technical audience and develop compelling visual narratives highly preferred.
Proficiency with Python, R, SQL, or similar tools to manipulate large, complex healthcare data sets highly preferred.
Experience with data visualization platforms (Power BI, Tableau, or equivalent) preferred.

Responsibilities

Develop and implement predictive models, trend detection algorithms, and statistical analyses using weekly claims, pharmacy, lab, and authorization data to identify emerging cost drivers.
Apply machine learning and AI techniques to uncover leading indicators of health utilization trends and improve predictive accuracy of actuarial and financial models.
Build and enhance interactive dashboards and executive tools that translate complex data into actionable insights for business and finance leaders.
Design and implement scalable machine learning models and LLM-based solutions.
Apply NLP techniques and prompt engineering to build conversational and generative AI systems.
Develop APIs using FastAPI or Flask for model serving and integration.
Execute algorithms to address specific business problems under the direction of team lead or manager.
Work with datasets of moderate size and complexity.
Develop visualization of analysis output for business users and publish results under the direction of team lead or manager.
Support the evolution of early-warning systems and automation for trend monitoring and reporting across multiple lines of business.
Translate model outputs and statistical insights into clear business narratives that inform planning, pricing, and strategic actions.