Analytics Summer 2027 Intern (Graduate)
Posted Sep 18, 2026 · We last checked this listing on Oct 5, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a data science or analytics project from your graduate program. What question were you answering?
What they are checking: Whether they frame analysis around a real question rather than just techniques.
How do you explain a model's results to someone without a technical background?
What they are checking: Their ability to communicate findings in a way business partners can act on.
Tell me about a time your analysis led to a different conclusion than you expected.
What they are checking: Whether they follow the data honestly and communicate surprising results.
What would you do
Your model performs well overall but poorly for one group of members. What do you do?
What they are checking: Whether they recognize fairness and bias issues and investigate them rather than ignoring them.
You're placed on a team doing something outside your coursework, like BI reporting. How do you get up to speed?
What they are checking: Their adaptability, since interns may land on any of several analytics teams.
About the work
How would you approach predicting which members are likely to be hospitalized in the next six months?
What they are checking: Their ability to frame a healthcare prediction problem, choose features and think about evaluation.
What steps do you take to clean and check a dataset before modeling?
What they are checking: Whether they understand that data quality drives result quality, especially in claims data.
What SQL and Python or R skills do you use most, and how?
What they are checking: Their hands-on technical ability with the tools analytics teams rely on.
Health data is sensitive. How do you think about privacy when working with member data?
What they are checking: Their awareness of protected health information and responsible data handling.
How would you decide whether a simple model or a complex machine learning model is the right choice?
What they are checking: Their judgment about tradeoffs between accuracy, interpretability and practical use.
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As published by Centene.