Milliman Software Engineer Interview Questions + Guide in 2025

Milliman is a leading consulting firm specializing in actuarial science, risk management, and advanced technology applications, particularly within the healthcare sector.

The Software Engineer role at Milliman focuses on developing and integrating innovative software solutions that enhance operational efficiency and address complex business challenges. Key responsibilities include collaborating with data scientists and engineers to design AI-powered applications, implementing and optimizing AI models, and ensuring seamless integration within diverse systems. Candidates should possess strong technical expertise in programming languages such as Python and C#, familiarity with cloud technologies and large datasets, and a solid understanding of software development methodologies, including agile practices. Ideal candidates demonstrate excellent problem-solving skills, innovative thinking, and the ability to communicate complex technical concepts effectively within cross-functional teams.

This guide will help you prepare thoroughly for your interview at Milliman by providing insights into the role, company expectations, and the skills that are highly valued.

The interview process for a Software Engineer at Milliman is structured and involves multiple stages to assess both technical and interpersonal skills.

1. Initial Screening

The process typically begins with an initial screening conducted by a recruiter. This is a brief phone interview where the recruiter will discuss your background, the role, and the company culture. They will also gauge your interest in the position and assess if your skills align with the job requirements.

2. Technical Assessment

Following the initial screening, candidates usually undergo a technical assessment. This may involve a coding challenge or a technical interview conducted via video conferencing. During this stage, you can expect questions related to programming languages such as Python and C#, as well as inquiries about your experience with AI frameworks and cloud technologies. The focus will be on your problem-solving abilities and your understanding of software development principles.

3. Take-Home Assignment

In some cases, candidates may be required to complete a take-home assignment. This assignment typically involves practical tasks related to software development, such as optimizing SQL queries or developing a small application. This step allows candidates to demonstrate their technical skills in a real-world context.

4. Panel Interview

The next step is often a panel interview, where you will meet with multiple team members, including engineers and possibly managers. This interview will cover both technical and behavioral questions. Expect to discuss your past projects, your approach to teamwork, and how you handle challenges. The STAR (Situation, Task, Action, Result) method is commonly used to frame behavioral questions.

5. Final Interview

The final stage may include a more in-depth interview with senior management or directors. This round often focuses on your long-term career goals, your fit within the company culture, and your understanding of the healthcare industry. Behavioral questions will likely be prominent, assessing how you align with Milliman's values and mission.

Throughout the process, candidates are encouraged to ask questions about the team dynamics, project expectations, and company culture to ensure a mutual fit.

Now, let's delve into the specific interview questions that candidates have encountered during this process.

Here are some tips to help you excel in your interview.

Understand the Interview Process

Milliman's interview process can be extensive and may include multiple rounds, such as technical assessments, behavioral interviews, and possibly a take-home assignment. Be prepared for a variety of question types, including coding challenges and discussions about your past experiences. Familiarize yourself with the structure of the interview and the types of questions that may be asked, as this will help you feel more at ease during the process.

Prepare for Technical Questions

Given the technical nature of the Software Engineer role, you should be well-versed in programming languages such as Python and C#, as well as AI frameworks like PyTorch and LangChain. Brush up on your knowledge of algorithms, data structures, and software development best practices. Expect questions that test your understanding of AI model integration and troubleshooting, as well as your ability to optimize system performance. Practicing coding problems on platforms like LeetCode can be beneficial.

Emphasize Collaboration and Communication Skills

Milliman values teamwork and collaboration, especially in cross-functional settings. Be prepared to discuss your experiences working in teams, how you handle conflicts, and your approach to communicating complex technical concepts to non-technical stakeholders. Use the STAR method to structure your responses to behavioral questions, focusing on specific examples that highlight your collaborative spirit and communication skills.

Showcase Your Problem-Solving Abilities

The ability to troubleshoot and resolve issues is crucial for this role. Be ready to discuss specific challenges you've faced in previous projects and how you approached solving them. Highlight your analytical thinking and innovative solutions, especially in the context of AI and software development. This will demonstrate your readiness to tackle the complexities of the role.

Stay Current with Industry Trends

Milliman is focused on leveraging cutting-edge AI technologies, so showing that you are knowledgeable about the latest trends and developments in AI and healthcare technology can set you apart. Discuss any recent advancements you've followed or projects you've worked on that align with these trends. This will not only show your passion for the field but also your commitment to continuous learning.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your adaptability, attention to detail, and learning agility. Milliman's culture emphasizes a supportive environment where employees are encouraged to grow and learn. Prepare to share examples of how you've adapted to changing project requirements or how you've taken initiative to learn new skills or technologies.

Ask Insightful Questions

At the end of the interview, you will likely have the opportunity to ask questions. Use this time to inquire about the team dynamics, ongoing projects, and how the company supports professional development. This not only shows your interest in the role but also helps you gauge if Milliman is the right fit for you.

Follow Up Professionally

After the interview, consider sending a thank-you email to express your appreciation for the opportunity to interview. This is a chance to reiterate your enthusiasm for the role and the company, and to briefly mention any key points from the interview that you found particularly engaging.

By following these tips and preparing thoroughly, you can position yourself as a strong candidate for the Software Engineer role at Milliman. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Software Engineer interview at Milliman. The interview process will likely assess your technical skills, problem-solving abilities, and your understanding of AI technologies, particularly in the context of healthcare applications. Be prepared to discuss your experience with programming languages, AI frameworks, and your approach to collaborative projects.

Technical Skills

1. Can you explain the difference between supervised and unsupervised learning?

Understanding the fundamental concepts of machine learning is crucial for this role, as it involves working with AI models.

How to Answer

Provide clear definitions of both supervised and unsupervised learning, along with examples of each. Highlight the scenarios in which you would use one over the other.

Example

“Supervised learning involves training a model on labeled data, where the outcome is known, such as predicting house prices based on features like size and location. In contrast, unsupervised learning deals with unlabeled data, where the model tries to identify patterns or groupings, like clustering customers based on purchasing behavior.”

2. Describe your experience with Python and C# in developing AI applications.

This question assesses your proficiency in the programming languages relevant to the role.

How to Answer

Discuss specific projects where you utilized Python and C#, focusing on the libraries and frameworks you used for AI development.

Example

“I have developed several AI applications using Python, leveraging libraries like TensorFlow and PyTorch for model training. In one project, I used C# to integrate a pre-trained model into a healthcare application, ensuring it met performance requirements while maintaining scalability.”

3. What are some common challenges you face when integrating AI models into existing systems?

This question evaluates your problem-solving skills and understanding of system integration.

How to Answer

Identify typical challenges such as data compatibility, performance issues, or user acceptance, and explain how you have addressed them in the past.

Example

“One common challenge is ensuring data compatibility between the AI model and existing systems. I tackled this by implementing data transformation processes that aligned the model’s input requirements with the data formats used in our systems, which improved integration efficiency.”

4. How do you ensure the performance and scalability of AI models?

This question focuses on your technical knowledge regarding model optimization.

How to Answer

Discuss techniques you use for performance tuning and scaling, such as model selection, hyperparameter tuning, and using cloud resources.

Example

“I ensure performance by conducting thorough testing and using techniques like cross-validation to select the best model. For scalability, I leverage cloud services like Azure to handle increased loads, allowing the application to scale dynamically based on user demand.”

5. Can you explain your experience with foundational model APIs like OpenAI or Anthropic?

This question assesses your familiarity with cutting-edge AI technologies.

How to Answer

Share specific experiences where you have utilized these APIs, including the context and outcomes of your projects.

Example

“I have worked with the OpenAI API to develop a chatbot for a healthcare application. By integrating the API, I was able to enhance the user experience by providing real-time responses to patient inquiries, which significantly improved engagement.”

Problem-Solving and Collaboration

1. Describe a time when you had to troubleshoot a complex AI-related issue.

This question evaluates your analytical skills and ability to work under pressure.

How to Answer

Provide a specific example, detailing the problem, your approach to troubleshooting, and the resolution.

Example

“In a previous project, we faced an issue where the AI model was underperforming. I conducted a root cause analysis, identifying that the training data was biased. I collaborated with the data team to gather more diverse data, retrained the model, and improved its accuracy by 20%.”

2. How do you stay current with the latest developments in AI technologies?

This question assesses your commitment to continuous learning and professional development.

How to Answer

Mention specific resources, such as journals, online courses, or conferences, that you utilize to keep your knowledge up to date.

Example

“I regularly read AI research papers from arXiv and attend webinars hosted by industry leaders. I also participate in online courses on platforms like Coursera to deepen my understanding of emerging technologies and methodologies.”

3. Can you give an example of a successful collaboration with cross-functional teams?

This question evaluates your teamwork and communication skills.

How to Answer

Describe a project where you worked with different teams, highlighting your role and the impact of the collaboration.

Example

“I collaborated with data scientists and healthcare professionals to develop an AI-driven patient management system. My role involved integrating the AI model into the application while ensuring that the user interface met the needs of healthcare providers, resulting in a product that improved patient care efficiency.”

4. How do you handle tight deadlines while ensuring quality in your work?

This question assesses your time management and prioritization skills.

How to Answer

Discuss your strategies for managing time effectively while maintaining high standards in your work.

Example

“I prioritize tasks based on their impact and urgency, using project management tools to track progress. During a recent project with a tight deadline, I focused on delivering a minimum viable product first, allowing for iterative improvements based on user feedback without compromising quality.”

5. What is your approach to documenting AI models and applications?

This question evaluates your understanding of best practices in software development.

How to Answer

Explain the importance of documentation and your methods for maintaining comprehensive records.

Example

“I believe documentation is crucial for ensuring transparency and facilitating collaboration. I maintain detailed records of model architectures, training processes, and performance metrics, using tools like Jupyter Notebooks for code comments and version control systems for tracking changes.”