Milliman Data Analyst interview questions & guide 2026

Because Milliman evaluates both technical execution and consulting potential, you should expect a blend of technical assessments, case studies, and behavioral deep dives. The following questions are representative of what candidates face during the Data Analyst interview process.

Technical & SQL Skills

These questions evaluate your ability to manipulate data, query databases, and read code in real-time. Depending on the team, you may be asked to review queries directly on an interviewer's screen or write them from scratch.

• Write a SQL query to identify duplicate records in a healthcare claims table and explain how you would clean them.
• Walk me through this SQL query on my screen: what is this specific JOIN accomplishing, and how would you optimize it?

To succeed in the Milliman interview process, you must prepare for an environment that values technical accuracy just as much as clear communication.

Technical Competency – You must demonstrate a strong command of relational databases and data manipulation tools. Expect to prove your SQL skills, advanced Excel capabilities, and familiarity with statistical tools like Python, R, or SAS. Interviewers look for clean, logical code and a systematic approach to data cleaning.

Structured Problem Solving – When presented with a dataset or a case study, your ability to organize your thoughts is critical. You should be able to break down a complex, ambiguous problem into testable hypotheses, perform the necessary analysis, and synthesize your findings into a structured report.

Consulting Mindset & Communication – Because Data Analysts at Milliman frequently support consulting teams, you must be able to explain the "so what" behind the data. Interviewers evaluate how clearly you explain technical concepts and whether you can present data in a way that helps partners make strategic decisions.

Adaptability & Independence – Due to Milliman's decentralized practice structure, you will often work with minimal supervision. You need to show that you are self-directed, comfortable with ambiguity, and capable of managing your own deadlines across multiple projects.

The interview process for a Data Analyst at Milliman is unique because it is highly customized by each office and practice group. While some offices run a streamlined process, others utilize highly rigorous, multi-stage evaluations to match their specific consulting needs. You should prepare for a process that can range from highly technical take-home assessments to extensive panel interviews.

Typically, the process begins with an HR screening call to discuss your background, salary expectations, and interest in the specific practice group. Following this, many teams require a technical assessment. This may take the form of a one-way video interview, an online coding test, or a comprehensive take-home case study where you are given a dataset and asked to spend several hours analyzing it and preparing a professional report.

If you pass the technical screening, you will move on to the final rounds. This stage can be highly intensive. Some practice groups will invite you for a full day of consecutive one-on-one interviews with members of different teams. Other groups may conduct a structured panel day where you meet with up to eight different stakeholders—including Project Managers, Consultants, and Partners—to evaluate your technical depth, behavioral alignment, and consulting potential.

The timeline above outlines the typical progression from the initial application to the final offer stage. Candidates should use this visual guide to pace their preparation, ensuring they allocate ample time for both the take-home case study and the intensive final-round panel interviews. Because the process is managed locally by individual practice offices, response times between stages can vary significantly.

Technical Data Skills

Your technical evaluation is designed to ensure you can handle large, complex datasets with minimal oversight. At Milliman, data integrity is paramount; a single analytical error can lead to millions of dollars in mispriced risk for a client.

Be ready to go over:

• SQL Proficiency – Advanced querying, window functions, complex joins, and database optimization techniques.
• Data Validation – Methods for identifying outliers, handling missing values, and ensuring data quality before running models.

As a Data Analyst at Milliman, your daily responsibilities will center on ensuring data accuracy, executing complex analyses, and supporting the consulting pipeline. You will act as the technical backbone of your practice group, transforming raw client data into structured assets that consultants can use to advise clients.

Your primary responsibilities will include:

• Data Ingestion and Cleansing – You will receive large, disparate datasets from clients (such as insurance claims, financial records, or demographic data). You must validate, clean, and format this data to ensure it aligns with Milliman's analytical standards.
• Querying and Modeling – You will write complex SQL queries and build analytical models to extract key trends, identify cost drivers, and calculate risk metrics.
• Reporting and Presentation – You will design and maintain reports, dashboards, and client-ready slide decks. You must translate quantitative findings into clear business insights that consultants can present to clients.
• Cross-functional Collaboration – You will collaborate daily with actuaries, consultants, and IT staff. You will help bridge the gap between technical data infrastructure and strategic business applications.
• Process Automation – You will identify opportunities to streamline repetitive data tasks, writing scripts or building macros to automate data validation and reporting workflows.

Because Milliman operates across highly specialized domains like healthcare, insurance, and employee benefits, successful candidates typically possess a strong quantitative background combined with excellent communication skills.

• Must-have skills – Strong proficiency in SQL (writing complex queries, joins, and aggregations); advanced Excel skills (VLOOKUPs, pivot tables, complex formulas, and data modeling); experience handling large, unstructured datasets; and a proven track record of structured problem-solving.
• Nice-to-have skills – Experience with statistical programming languages (Python, R, or SAS); familiarity with business intelligence tools (Power BI, Tableau); and prior exposure to healthcare claims data, insurance underwriting, or actuarial concepts.
• Experience level – Typically requires a bachelor's degree in a quantitative field (such as Statistics, Mathematics, Economics, Finance, or Computer Science) and 1 to 4 years of experience in a data-focused analytical role, preferably within a consulting or professional services environment.
• Soft skills – Strong written and verbal communication; the ability to work independently in a decentralized environment; exceptional attention to detail; and a proactive approach to learning complex business domains.

Q: How technical is the Data Analyst interview at Milliman? A: It is highly technical but balanced with behavioral evaluations. You must be prepared to demonstrate strong SQL and Excel skills, often through a multi-hour take-home case study or by explaining query structures in real-time.

Q: Why does the interview process vary so much between different candidates? A: Milliman is organized as a decentralized network of independent practice groups. Each office and team manages its own hiring process, meaning one team may use a quick behavioral screen and a case study, while another might require a full-day panel interview with eight different team members.

Q: Do I need an actuarial background to apply for this role? A: No. While a Data Analyst at Milliman often supports actuarial teams, you do not need to be an actuary. However, having a strong interest in risk management, finance, or healthcare analytics is highly beneficial.

Q: How long does the hiring process typically take from application to offer? A: Due to the decentralized nature of the firm and the thoroughness of the evaluations, the process can take anywhere from three weeks to two months. It is common to experience gaps of a few weeks between stages, especially after submitting a take-home assessment.

Q: What is the work culture like for analysts at Milliman? A: The culture is highly professional, entrepreneurial, and academic. Analysts who thrive are those who enjoy taking ownership of their work, can operate independently, and take pride in delivering highly accurate, error-free analyses.

• Prepare for Decentralized Differences: Understand that the practice group you are interviewing with operates almost like an independent business. Tailor your preparation specifically to their domain (e.g., healthcare, employee benefits, or property & casualty) rather than preparing for a generic corporate interview.

• Over-Communicate Your Methodology: During case studies or technical reviews, focus heavily on how you arrived at your conclusion. Milliman values structured thinking and documentation. Clearly write out your assumptions, data limitations, and step-by-step logic in your reports.

• Master the STAR Method: For behavioral interviews, structure your answers using the Situation, Task, Action, and Result framework. Be highly specific about your individual contribution to projects and the quantitative impact of your work.

• Clarify Expectations Early: Because the interview process can be intensive and sometimes lacks standard corporate coordination, do not hesitate to ask HR about the specific steps, timeline, and salary range during your initial screening call.

• Research the Practice Group: Before your interview, find out which specific Milliman practice group you are meeting with. Read their published whitepapers or industry reports to understand the specific challenges their clients face.

Securing a Data Analyst position at Milliman is an exceptional opportunity to build a highly respected career at the intersection of data science, consulting, and risk management. The role offers an intellectual rigor and project ownership that is rare in typical corporate environments. By mastering your technical data skills, preparing thoroughly for the take-home case study, and demonstrating a polished consulting mindset, you can position yourself as a top-tier candidate.

As you prepare, focus on building clean, structured habits in your data analysis. Treat every technical test and conversation as an opportunity to demonstrate your commitment to data integrity and clear communication. With focused preparation, you can navigate Milliman's unique and rigorous interview process with confidence.

To gain deeper insights, review real candidate experiences, and access additional preparation resources, explore the comprehensive tools available on Dataford.

The compensation insights above reflect the competitive nature of the Data Analyst role at Milliman. When evaluating an offer, keep in mind that total compensation packages may also include performance-based bonuses linked directly to the profitability of your specific practice group. Use this data to guide your salary expectations during your initial discussions with the recruiting team.