AI Data Scientist – Indianapolis Health

Overview

Millimans 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.

Required

• Bachelors degree in Data Science Computer Science Statistics or a related field
• 5 years of experience in data science machine learning or AI engineering roles

Preferred

• Masters 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 including documenting decisions and next steps
• Experience translating model outputs into structured explainable artifacts (drivers supporting exhibits summary narratives) that enable non-technical reviewers and stakeholders to act on results with confidence
• 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 including methods descriptions solution diagrams and demo narratives
• Experience with anomaly detection and risk stratification methods (peer grouping statistical scoring outlier identification) applied to large-scale operational datasets
• Experience 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 systems
• Experience designing agentic AI workflows including tool-use orchestration via protocols such as MCP with appropriate guardrails logging and human-in-the-loop controls
• Time series analysis applied to trend detection seasonality and behavioral pattern recognition in operational datasets
• Graph or network analytics applied to relationship modeling entity resolution or pattern detection in complex relational datasets
• Model monitoring and operational ML practices including drift detection retraining strategies and automated evaluation in production
• Experience with cloud-based data and AI platforms including managed search or retrieval capabilities to support governed analytics and AI workflows
• Experience 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 analytics

Individual(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 Team

The 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.

Location

The 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 basis.

Compensation

The overall salary range for this role is $93700 - $154500. A combination of factors will be considered including but not limited to education relevant work experience qualifications skills certifications 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 partners
• Employee Assistance Program (EAP) - Confidential support for personal and work-related challenges
• 401(k) Plan - Includes a company matching program and profit-sharing contributions
• Discretionary Bonus Program Recognizing employee contributions
• Flexible Spending Accounts (FSA) - Pre-tax savings for dependent care transportation and eligible medical expenses
• Paid 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 year
• Family Building Benefits including Adoption and fertility assistance
• Paid Parental Leave - Up to 12 weeks of paid leave for employees who meet eligibility criteria
• Life Insurance & AD&D - 100% of premiums covered by Milliman
• Short-Term and Long-Term Disability Fully paid by Milliman

Who We Are

Independent 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.

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