Assistant Vice President, Health Analytics Data Scientist
Atlanta, Georgia; Chicago, Illinois; Denver, Colorado; Dallas, Texas; Seattle, Washington
- Pay
$160,000–190,000/yearLocation-specific pay — pay source
Pay Transparency Laws: The salary range for this position (intended for U.S. applicants) is $160,000 to $190,000 annually.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and execute causal inference studies on program, vendor, and treatment impact
Build and tune predictive models such as high-cost claimant prediction and cost forecasting
Take models from development into governed, monitored production with MLOps practices
Document methods and present results and limitations to clients and senior leaders
Review code and models and set validation and fairness standards
From the employer’s posting
Design and execute medical economics and causal inference studies that estimate the impact of programs, treatments, vendors, and point solutions
Design, build, and tune tabular analyses and predictive models including gradient-boosted, statistical methods and emerging AI modeling techniques
Ensure MLOps and model governance end-to-end, including experiment tracking, model registries, reproducible training pipelines
Document methods, assumptions, data definitions, and results thoroughly
Serve as senior technical, code, and methodology reviewer for analytics deliverables
Tools in this posting
- Python
- R
- SQL
- Azure
- Databricks
- Docker
- MLflow
- Spark
Source — Tool mentions in context
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, consulting, clinical, innovation, and specialty practice areas, and stay current on emerging vendors and startups in healthcare navigation, digital health, and care delivery Mentor and coach data scientists, and lead multiple projects with clear priorities, timelines, and milestones Skills and experience that will lead to success Minimum 7 years of total experience, including health insurance, with a track record of delivering value to clients and colleagues Strong foundation in applied statistics or medical economics, including model training and validation, statistical testing, regression and generalized linear models, and experimental and quasi-experimental design Deep hands-on experience building, tuning, and interpreting tabular predictive models, including feature engineering, cross-validation, hyperparameter optimization, calibration, class imbalance, and explainability methods Hands-on experience applying causal inference to observational health data / medical economics, including matched cohort target trial emulation, propensity score methods, difference-in-differences (including staggered-adoption and event-study approaches), sensitivity analysis, and risk adjustment, with financial, utilization, and clinical outcomes metrics Detailed understanding of US health data, including eligibility, medical and pharmacy claims, and coding standards such as ICD-10-CM, ICD-10-PCS, CPT, DRG, and related industry standards Experience with MLOps and model governance – such as MLflow or similar tooling, model registries, automated training and scoring pipelines, version control, drift and performance monitoring, and model risk documentation and review Experience partnering with enterprise technology and architecture teams and working with offshore or distributed engineering teams to deploy and support models in production Expert Python and/or R and strong SQL
Databricks, Spark, Azure, Docker, and CI/CD experience a plus High-performing individual contributor who can mentor junior data scientists and work independently across multiple projects Excellent written and verbal communication, with a track record of documenting methods and assumptions clearly and presenting statistical results, uncertainty, and limitations to actuaries, consultants, clients, and non-technical audiences Education: Bachelor’s or master’s degree in statistics, biostatistics, mathematics, economics, health services / public health research, data science, computer science, actuarial science, or a related quantitative field, or equivalent professional experience
Posting record
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- Live
- First seen by us
- Oct 10, 2026 · 19 days ago
- Recorded sightings
- 137
- Last seen by us
- Oct 29, 2026
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Job description
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- Pay
Pay Transparency Laws: The salary range for this position (intended for U.S. applicants) is $160,000 to $190,000 annually.
- Location & working pattern
Atlanta, Georgia; Chicago, Illinois; Denver, Colorado; Dallas, Texas; Seattle, Washington
This passage needs a closer read in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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