AI Data Scientist - Indianapolis Health

OverviewMillimans Indianapolis Health practice is seeking a highly skilled and motivated AI Data Scientist to join our growing practice. This role is focused on applied machine learning for healthcare, enhancing and extending an existing production AI and analytics platform, and contributing new ideas and prototypes across our broader artificial intelligence (AI) and machine learning (ML) portfolio. The ideal candidate has hands-on experience with healthcare data, strong ML and statistical fundamentals, and the ability to operationalize results through dashboards. You will also contribute to applied large language model (LLM) capabilities, including prompt design and agent-style workflow automation, using disciplined evaluation, traceability, and guardrails appropriate for regulated environments.Responsibilities In this role, you will support:Production AI & Prototyping: Enhance and extend existing production AI/analytics platforms and develop new applications through research, ideation, and rapid prototyping to solve complex public sector healthcare challenges.Model Development & Interpretability:Develop interpretable, defensible ML models and statistical methods to support user workflows, including explainable feature attribution, comparative benchmarking, and structured model output summaries.Client Deliverables & Communication: Produce high-quality written reports, exhibits, and presentations that clearly communicate methods, findings, limitations, and recommended actions to non-technical audiences.Governed GenAI & LLMs: Engineer governed solutions including prompt design, RAG, and agentic workflow orchestration (e.g., MCP) with rigorous evaluation and traceability for regulated use.Operational ML Excellence: Own model performance by defining acceptance metrics, monitoring data health (including drift), tuning thresholds, and designing dashboards for triage and KPI tracking.Business Development Support: Support proposals and RFPs by drafting technical approach sections, methods descriptions, solution diagrams, and participating in capability demos.Cross-Functional Collaboration: Partner with domain SMEs (actuarial, clinical, pharmacy, policy) to translate requirements into quantifiable solutions, validate outcomes, and align outputs to real operational decisions.Engineering Best Practices: Collaborate with data engineering to build scalable pipelines with robust quality controls, reproducibility, logging, and documentation.Qualifications Consulting-Grade Communication: Demonstrated ability to write clear client-ready reports, build presentations, and explain limitations and tradeoffs to non-technical stakeholders.Applied ML & Statistical Rigor: Strong applied ML skills on large-scale data with interpretable methods, comparative analytics, and defensible anomaly scoring approaches suitable for regulated review and support contexts.End-to-End ML Delivery: Proven experience taking projects from ambiguous problem framing to maintainable deployment and adoption in operational workflows.Healthcare Data Expertise:Hands-on experience with healthcare data (claims/encounters preferred), including feature engineering, validation, and explainability for audit/oversight workflows.Applied Generative AI: Practical experience with prompt design, API-based integration, and governed retrieval (RAG) with evaluation and guardrails.Production Engineering: Strong Python skills in shared codebases (OOP, modular design) with modern engineering discipline (testing, code reviews, structured logging, Git/GitHub).Data at Scale: Strong SQL plus distributed processing (Spark, PySpark, Databricks preferred) with strong data quality and validation practices.RequiredBachelors degree in Data Science, Computer Science, Statistics, or a related field5+ years of experience in data science, machine learning, or AI engineering rolesPreferredMasters degree in Data Science, Computer Science, Statistics, or a related fieldExperience facilitating client workshops to define scope, success metrics, validation plans, and acceptance criteria, including documenting decisions and next stepsExperience translating model outputs into structured, explainable artifacts (drivers, supporting exhibits, summary narratives) that enable non-technical reviewers and stakeholders to act on results with confidenceExperience leading executive briefings and aligning stakeholders on findings, tradeoffs, and recommended actions in regulated environmentsExperience supporting proposals or capability briefings with technical content, including methods descriptions, solution diagrams, and demo narrativesExperience with anomaly detection and risk stratification methods (peer grouping, statistical scoring, outlier identification) applied to large-scale operational datasetsExperience with MLOps and DevOps practices, including CI/CD pipelines, containerization (e.g., Docker), infrastructure-as-code, and automated testing and deployment workflows for AI/ML systemsExperience designing agentic AI workflows, including tool-use orchestration via protocols such as MCP, with appropriate guardrails, logging, and human-in-the-loop controlsTime series analysis applied to trend detection, seasonality, and behavioral pattern recognition in operational datasetsGraph or network analytics applied to relationship modeling, entity resolution, or pattern detection in complex relational datasetsModel monitoring and operational ML practices, including drift detection, retraining strategies, and automated evaluation in productionExperience with cloud-based data and AI platforms, including managed search or retrieval capabilities to support governed analytics and AI workflowsExperience improving retrieval quality for governed AI workflows (chunking strategies, relevance evaluation, grounding checks, and citation accuracy)Experience building document ingestion and extraction pipelines that convert PDFs, Word, and Excel into structured, validated datasets suitable for downstream analyticsIndividual(s) must be legally authorized to work in the United States without the need for immigration support or sponsorship from Milliman now or in the future.The TeamThe Indianapolis Health Practice has 250+ full-time employees from diverse academic and professional backgrounds. Our practice is structured to serve state Medicaid and other health and human service agencies through dedicated core teams tailored to each clients unique needs. As a member of the Indianapolis Data Engineering, Architecture, and Science (IDEAS) team, you will provide advanced analytics and data science support to key state clients and their core teams under the mentorship of senior data consultants. Our team works cross-functionally with actuarial, policy, finance, pharmacy, clinical, and data management professionals to deliver practical, defensible results. You will work on challenging problems, collaborate with experienced colleagues, and contribute across a variety of client programs and solution areas with opportunities to learn, grow, and take on increasing ownership over time.LocationThe person hired for this role will work in a dynamic, hybrid environment, with 2 to 3 days per week of on-site work required in our Indianapolis office on a weekly pensationThe overall salary range for this role is $93,700 - $154,500. A combination of factors will be considered, including, but not limited to, education, relevant work experience, qualifications, skills, certifications, etc. In addition, we offer a performance-based bonus-plan, profit sharing, and generous benefits.Benefits We offer a comprehensive benefits package designed to support employees health, financial security, and well-being. Benefits include:Medical, Dental and Vision - Coverage for employees, dependents, and domestic partnersEmployee Assistance Program (EAP) - Confidential support for personal and work-related challenges401(k) Plan - Includes a company matching program and profit-sharing contributionsDiscretionary Bonus Program - Recognizing employee contributionsFlexible Spending Accounts (FSA) - Pre-tax savings for dependent care, transportation, and eligible medical expensesPaid Time Off (PTO) - Begins accruing on the first day of work. Full-time employees accrue 15 days per year, and employees working less than full-time accrue PTO on a prorated basis.Holidays - A minimum of 10 observed holidays per yearFamily Building Benefits including Adoption and fertility assistancePaid Parental Leave - Up to 12 weeks of paid leave for employees who meet eligibility criteriaLife Insurance & AD&D - 100% of premiums covered by MillimanShort-Term and Long-Term Disability - Fully paid by MillimanWho We AreIndependent for over 75 years, Milliman delivers market-leading services and solutions to clients worldwide. Today, we are helping companies take on some of the worlds most critical and complex issues, including retirement funding and healthcare financing, risk management and regulatory compliance, data analytics and business transformation.Milliman invests in skills training and career development, and gives all employees access to a variety of learning and mentoring opportunities. Our growing number of Milliman Employee Resource Groups (ERGs) are employee-led communities that influence policy decisions, develop future leaders, and amplify the voices of their constituents. We encourage our employees to give back to their varied professions, including leadership in professional organizations. Please visit our web site to learn more about Millimans commitments to our people, diversity and inclusion, social impact and sustainability.Through a team of professionals ranging from actuaries to clinicians, technology specialists to plan administrators, we offer unparalleled expertise in employee benefits, investment consulting, healthcare, life insurance and financial services, and property and casualty insurance.Equal Opportunity All qualified applicants will receive consideration for employment, without regard to race, color, religion, sex, sexual orientation, national origin, disability, or status as a protected veteran.#LI-KM1#LI-HYBRID

Created: 2026-03-07