Argonne National Laboratory Data Analyst Intern
Woodridge, IL·208 interview reviews·Medium difficulty
Data Analyst Intern Interview Reviews
208Online assessment was difficult, but the final round technical was just 2 leetcode questions. Studying tagged questions and general leetcode helps a lot. Interviewer was friendly and wanted me to succeed.
“Design Web Crawler - Design a distributed web crawling system”
Just one round with 2 LC hards in 45 min. It wasn't too bad at all — if you've done a lot of LC you're gonna be fine. Make sure to check off your approach with the interviewer before you begin implementing.
“Design TinyURL - Design a URL shortening service like bit.ly”
Had a recruiter screen first, then a technical round focused on system design and coding. The interviewer was very professional and walked through the problem step by step. Good overall experience.
“Give an example of when you had to make a difficult trade-off decision”
Straightforward — just 2 medium leetcode-tagged problems in 45 minutes. Very fast paced though so be aware of time. A few follow-up questions for the interviewer at the end. No behavioral questions.
“K Closest Points to Origin - Find K points closest to origin using Manhattan distance”
About This Role
Frequently Asked Questions
How hard is it to get hired as a Data Analyst Intern at Argonne National Laboratory?
The interview difficulty is rated 2.7/5 by candidates. 57% report a positive experience. Focus on Python, Machine Learning, Statistics to improve your chances.
How long does the Argonne National Laboratory Data Analyst Intern hiring process take?
The process typically takes 2–6 weeks from application to final decision, depending on the hiring cycle and team availability.
What is the interview process like?
Most candidates go through a recruiter screen, followed by technical coding rounds, and a final interview loop. 67% of candidates applied online.
What questions are asked in a Argonne National Laboratory Data Analyst Intern interview?
Common topics include data structures & algorithms (arrays, trees, graphs), system design, and behavioral questions using the STAR method. Practice with our AI mock interviewer to prepare.
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