Role Description Milliman’s CMH Health Practice is looking for current college students pursuing a bachelor’s or master’s degree in math, finance, pharmacy, computer science, economics, statistics, or related major with quantitative coursework to partake in a Fall pharmacy analytics internship. This is a full-time, temporary internship from September to December 2026. In this role, the Pharmacy Analytics Intern will work in a fast-growing area of the Health practice by helping support our pharmacy group in helping clients navigate the complex industry and provide data-driven solutions that can improve or lower the cost of care. - Review pharmacy claims data. - Input data elements into various clinical and financial forecasting models. - Engage with a variety of internal colleagues for support, learning, and mentorship. Qualifications - Pursuing a bachelor’s or master’s degree in math, finance, pharmacy, computer science, economics, statistics, or related major with quantitative coursework. - Recent graduates will also be considered. - Prior experience working with U.S. healthcare claims is preferred. - Familiarity with pharmacy reimbursement in the United States. - Strong technical skills, including experience and proficiency with Microsoft Office tools such as Excel, Word, and PowerPoint. Requirements - Available to work full-time (40 hours per week) from September to December 2026. Benefits - Employee Assistance Program (EAP) – Confidential support for personal and work-related challenges. - 401(k) Plan – Eligibility after 1,000 hours worked within 12 consecutive months, including a company matching program and profit-sharing contributions. - Paid Time Off (PTO) – Begins accruing on the first day of work; interns will earn PTO based on 1 hour for every 30 hours worked. - Transportation – Pre-tax savings for eligible transit and parking expenses.

• Serve as the primary liaison between business stakeholders, the Data Governance Council, data domain owners, and technical teams to elicit, document, and prioritize data governance requirements across enterprise data domains. • Facilitate data governance workshops and working sessions to establish business definitions, data standards, business rules, data definitions, and domain onboarding plans. • Profile data and analyze source systems and data structures to assess content, quality, and structure, supporting accurate mapping and migration of master data and data hub models. • Develop comprehensive data mapping documents, including source-to-target specifications and transformation logic. • Work with Master Data Management (MDM), integration, and platform teams to validate source-to-target mappings and ensure consistency with approved business definitions, data standards, and governance policies. • Assist in identifying data quality issues and contribute to metadata and lineage documentation. • Create and maintain data catalogs to ensure consistent documentation, easy discovery, and effective management of enterprise data assets. • Coordinate with platform subject matter experts (SMEs) to validate data mapping requirements and support successful implementation within MDM, data hub, and integration platforms. • Track mapping progress, dependencies, and issues across teams and tools, providing timely updates and resolving blockers. • Collaborate with business stakeholders and project teams to understand data requirements for HR, Finance, Legal, and Professional Services functions. • Analyze and document existing data sources, structures, and business rules within legacy systems. • Develop data mapping specifications to ensure accurate migration to new systems. • Support the extraction, transformation, and loading (ETL) of data, including profiling, cleansing, and validating migrated data. • Perform data quality assessments and implement data validation processes to ensure completeness and accuracy. • Assist in designing and testing data integrations between new enterprise platforms and other business applications. • Create and maintain comprehensive documentation of data models, flows, and transformation rules. • Identify and resolve data-related issues during migration and post-implementation. • Provide regular updates and insights to project leaders and stakeholders regarding data migration progress and risks. • Support ongoing data governance and quality initiatives as new systems are adopted.

• Work directly with the client and play a critical role in shaping how credit decisions, portfolio performance, and risk-adjusted revenue decisions are made • Work on the full credit lifecycle from strategy and pricing to portfolio health and performance, ensuring the risk approach supports sustainable growth and strong financial outcomes • Directly influence profitability, capital efficiency, and long-term scalability

• Full-Stack Model Validation: Conduct rigorous, independent validations of sophisticated credit/fraud models—including machine learning and traditional statistical models—focusing on conceptual soundness, data integrity, and performance stability. • Advanced Quantitative Monitoring: Develop automated, independent monitoring suites in Python to track KRI/KPI drift, population stability (PSI), and feature importance shifts in real-time. • Remediation & Technical Advisory: Partner with 1st-line Model Developers to drive the remediation of validation findings, ensuring models and strategies are not only compliant but mathematically robust. • Audit & Regulatory Liaison: Partner with Internal Audit, Internal Controls, and Compliance to facilitate the timely resolution of audit and regulatory requests. • Affirm Bank: Work for the internal Bank team to support the build out of the Bank Model Risk Management function. Support the model validation requirements for Bank owned models.