Sanofi Data Scientist Interview Guide

Three candidates describe Sanofi interviews for data science roles, and the loops they report look quite different. One sat in an evening panel, one had an informal Zoom call with a hiring manager, and one went through a video screen followed by an in-person round. All three reported no offer, so treat this as a small sample rather than a fixed format.

The most consistent theme is that you should be ready to talk through your own project work. One candidate walked a panel through a current project and discussed the business context and tech stack. Another was pressed on OpenCV work from their resume, and a third opened the in-person round with a presentation on a recent project.

Technical questions were a mix of basics and applied topics. Reports mention Python and SQL, including an inner join question, plus supervised versus unsupervised learning and the bias-variance tradeoff. Another candidate was asked about random forests, tree models, RAG and agents. One was asked to sort a linked list, which felt out of step with the rest of the conversation, so a quick refresher on basic coding is reasonable.

Behavioral questions appeared too, including how to handle workplace conflict. One panel also drifted into questions about the candidate's employer and how they store files on a work laptop; that candidate stayed professional and explained the compliance concern. Pacing varied: one candidate found the gaps between the screen and the in-person round draining, so ask the recruiter what stages to expect and how long each step usually takes.