Criteo Data Scientist candidates report a five-round process featuring live coding, a consulting-style estimation exercise, and a take-home data analysis presentation. Prepare to show structured reasoning as well as clear communication of findings.
$144K
Avg. Base Comp
$153K
Avg. Total Comp
5 rounds
Typical Rounds
1-3 weeks
Process Length
For a Criteo Data Scientist interview, the clearest recent report describes five rounds and three distinct assessed formats: live coding, a consulting-style estimation problem, and a take-home data analysis presented to the team. The candidate who completed the process said the live-coding session required solving in real time while explaining their reasoning, so narrating choices and tradeoffs matters alongside getting to an answer.
The estimation exercise resembled a consulting market-sizing case. In the reported example, the candidate estimated the paint needed for an airline fleet. Focus practice on making assumptions explicit, breaking an ambiguous problem into manageable calculations, and sense-checking the final estimate rather than chasing a single precise number.
The final reported stage was a take-home analysis prepared in advance and presented with slides. Be ready to communicate the main insights, justify analytical decisions, and handle follow-up questions about the recommendation. One related intern report describes an initial HR conversation about motivation and understanding of the role, but it does not establish the full-time Data Scientist sequence. The evidence does not detail the other two rounds, so avoid assuming their format.
Synthesized from 2 candidate reports by our editorial team.
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Synthesized from candidate reports. Individual experiences may vary.
One candidate reports a live-coding round in which they worked through a problem while explaining their reasoning. Practice communicating your approach as you solve, including how you choose a path and evaluate the result.
A reported consulting-style brainteaser asked for an estimate of paint needed for an airline fleet. Candidates may be evaluated on clear assumptions, smaller calculations, and a sensible check of the estimate rather than an exact figure.
The reported final stage was a data analysis exercise prepared at home and presented to the team. Expect to explain key insights, support the choices behind the analysis, and answer follow-up questions about the recommendations.
