Assistant Vice President, Health Analytics Data Scientist

Chicago, IL;
Atlanta, GA;
Denver, CO;
Seattle, WA are preferrable locations but open to other Aon locations or possibly remote for the right fit

We are seeking a hands-on, statistically grounded health data scientist, health actuary or medical economics expert to work on cost-of-care measurement, causal inference and predictive modeling work streams and development of Aon analytics capabilities. You will own the design, validation, documentation, and delivery of the statistical and machine learning / predictive modeling algorithms and analyses that help employers and their partners understand cost, risk, and the impact of health programs - including total-cost-of-care predictive modeling and causal evaluations of programs and vendors using matched cohort trial emulation, difference-in-differences, and risk adjustment.

You will work to evolve capabilities and model performance, review code and models, document and present results to clients and senior leaders, and take models from development into governed, monitored production, working closely with actuaries, consultants, clinical and innovation specialists, Aon Business Solutions / Technology (ABS), technology architects, and engineering teams.

The ideal candidate has 7+ years of experience including commercial health insurance and/or health benefits consulting, a strong foundation in applied statistics and causal inference, and a track record of building and deploying tabular predictive models on large medical and pharmacy claims datasets. The ability to document methods rigorously and present results clearly to technical and non-technical audiences is critical. Practical experience with MLOps and model governance, and with partnering with enterprise technology and distributed engineering teams to move models into scalable, supported production, is essential.

At Aon, we shape decisions for the better to protect and enrich the lives of people around the world.

As an organization, we are united through trust as one inclusive team and we are passionate about helping our colleagues and clients succeed.

• Develop and deliver causal inference and predictive modeling work streams for the US Health Analytics practice, ensuring methodological rigor while staying hands-on in building, reviewing, and validating models and code within project timelines
• Collaborate closely with Aon Business Solutions / Technology (ABS), cloud architects, and offshore engineering and data science teams to align on data pipelines, model architecture, and deployment standards, coordinate delivery across locations and time zones, and move models from development into scalable, supported production
• Design, build, and tune tabular analyses and predictive models including gradient-boosted, statistical methods and emerging AI modeling techniques- such as cost and utilization forecasting, high-cost claimant prediction, risk stratification, and program engagement propensity - on large eligibility, medical claims, and pharmacy claims datasets from multiple sources
• Design and execute medical economics and causal inference studies that estimate the impact of programs, treatments, vendors, and point solutions on financial, utilization, and clinical outcomes, using matched cohort target trial emulation (explicit eligibility, time zero, and follow-up definitions; propensity score matching or weighting), difference-in-differences and event-study designs with parallel-trends and sensitivity testing, and risk adjustment
• Document methods, assumptions, data definitions, and results thoroughly - methodology write-ups, technical appendices, model cards, and reproducible analysis records - and present findings, uncertainty, and limitations clearly to clients, carriers, consultants, and senior leaders through polished reports and presentations
• Ensure MLOps and model governance end-to-end, including experiment tracking, model registries, reproducible training pipelines, automated testing, CI/CD, drift and performance monitoring, and model documentation, validation, and approval workflows aligned with Aon's risk, privacy, and compliance standards
• Serve as senior technical, code, and methodology reviewer for analytics deliverables, and set standards for model validation, explainability, bias and fairness review, and quality control
• Partner with senior leaders across Aon's health actuarial,…