Data Scientist Jobs

About The Position

Requirements

• 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.
• 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.

Nice To Haves

• Databricks, Spark, Azure, Docker, and CI/CD experience a plus.
• Advanced degrees are a plus.

Responsibilities

• Develop and deliver causal inference and predictive modeling workstreams 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, 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.

Benefits

• a 401(k) savings plan with employer contributions
• an employee stock purchase plan
• consideration for long-term incentive awards at Aon’s discretion
• medical, dental and vision insurance
• various types of leaves of absence
• paid time off, including 12 paid holidays throughout the calendar year
• 15 days of paid vacation per year
• paid sick leave as provided under state and local paid sick leave laws
• short-term disability and optional long-term disability
• health savings account
• health care and dependent care reimbursement accounts
• employee and dependent life insurance and supplemental life and AD&D insurance
• optional personal insurance policies
• adoption assistance
• tuition assistance
• commuter benefits
• an employee assistance program that includes free counseling sessions
• eligibility to participate in one of Aon’s annual incentive plans to receive an annual discretionary bonus