Data Scientist - Indianapolis Health

Milliman•Indianapolis, IN

5d•Hybrid

About The Position

Milliman’s Indianapolis Health practice is seeking a skilled and motivated Data Scientist to work on applied healthcare data science and analytics. The role enhances existing analytical products and develops new solutions for the practice’s AI and machine learning portfolio. The successful candidate will apply healthcare data expertise, statistical and machine learning skills, and consulting capabilities to translate complex problems into practical, scalable solutions. The Data Scientist will contribute throughout the lifecycle of data science initiatives, from problem definition and exploratory analysis through production deployment, client communication, and product enhancement. As part of the Indianapolis Data Engineering, Architecture, and Science (IDEAS) team, the role provides advanced analytics and data science support to state clients and their core teams, under the mentorship of senior data consultants. The position collaborates with actuarial, policy, finance, pharmacy, clinical, and data management professionals to deliver practical, defensible results across client programs and solution areas. This is a hybrid role requiring 2 to 3 days per week onsite at Milliman’s Indianapolis office. The Indianapolis Health Practice has more than 250 full-time employees.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.
2–5+ years of experience in data science, machine learning, or AI engineering roles.
Strong analytical skills in statistical modeling, machine learning, predictive analytics, anomaly detection, and quantitative problem solving, including the ability to explain methods and limitations.
Proven experience taking projects from ambiguous problem framing through maintainable deployment and adoption in operational workflows.
Hands-on healthcare data experience, preferably with claims or encounter data, including feature engineering, validation, and explainability for audit or oversight workflows.
Experience applying modern AI or machine-learning techniques to real-world business problems, including evaluation, validation, and deployment considerations.
Strong Python skills in shared codebases, including object-oriented programming, modular design, testing, code reviews, structured logging, and Git/GitHub.
Strong SQL skills and experience with distributed processing; Spark, PySpark, or Databricks experience is preferred.
Experience presenting analytical findings, facilitating stakeholder discussions, and communicating results, assumptions, limitations, and recommendations to support decision-making.
Basic knowledge of generative AI tools, their use for productivity, and potential ethical considerations.
Must be legally authorized to work in the United States without current or future immigration support or sponsorship from Milliman.

Nice To Haves

Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Experience facilitating client workshops to define scope, success metrics, validation plans, and acceptance criteria, and documenting decisions and next steps.
Experience translating model outputs into structured, explainable artifacts such as drivers, supporting exhibits, and summary narratives for non-technical reviewers.
Experience leading executive briefings and aligning stakeholders on findings, tradeoffs, and recommended actions in regulated environments.
Experience supporting proposals or capability briefings with technical content, methods descriptions, solution diagrams, and demo narratives.
Experience with anomaly detection and risk stratification methods, such as peer grouping, statistical scoring, and outlier identification, applied to large operational datasets.
Experience with MLOps and DevOps, including CI/CD pipelines, containerization such as Docker, infrastructure as code, and automated testing and deployment workflows for AI/ML systems.
Experience evaluating and operationalizing emerging analytical technologies, including machine learning and generative AI.
Experience with time-series analysis for trend detection, seasonality, and behavioral pattern recognition in operational datasets.
Experience with graph or network analytics for relationship modeling, entity resolution, or pattern detection in complex relational datasets.
Experience with production model monitoring, including drift detection, retraining strategies, and automated evaluation.
Experience with cloud-based data and AI platforms, including managed search or retrieval capabilities for governed analytics and AI workflows.

Responsibilities

Enhance existing AI and analytics products and develop new concepts, methods, and prototypes to address healthcare challenges.
Develop interpretable and defensible machine-learning models and statistical methods, including explainable feature attribution, comparative benchmarking, and structured model-output summaries.
Produce client-ready reports, exhibits, and presentations explaining methods, findings, limitations, and recommended actions to non-technical audiences.
Evaluate and apply appropriate analytical techniques, including machine learning, generative AI, natural language processing, and other emerging approaches.
Define model acceptance metrics, monitor model performance and data health including drift, tune thresholds, and design dashboards for triage and KPI tracking.
Support proposals and RFPs by drafting technical approaches and methods descriptions, preparing solution diagrams, and participating in capability demonstrations.
Collaborate with domain subject-matter experts to translate requirements into quantifiable solutions, validate outcomes, and align outputs with operational decisions.
Work with data engineering to build scalable pipelines with quality controls, reproducibility, logging, and documentation.
Support the long-term evolution of analytical products and platforms by gathering user feedback, identifying and prioritizing enhancements, and balancing innovation with maintainability and reliability.

Benefits

Medical, dental, and vision coverage for employees, dependents, and domestic partners.
Employee Assistance Program providing confidential support for personal and work-related challenges.
401(k) plan with company matching and profit-sharing contributions.
Discretionary bonus program.
Flexible Spending Accounts for dependent care, transportation, and eligible medical expenses.
Paid Time Off accruing from the first day of work; full-time employees accrue 15 days per year.
At least 10 observed holidays per year.
Adoption and fertility assistance.
11 weeks of paid parental leave for employees who meet eligibility criteria.
Life insurance and AD&D coverage with premiums fully covered by Milliman.
Short-term and long-term disability coverage fully paid by Milliman.
Skills training, career development, learning, and mentoring opportunities.