Candidates describe P&G data scientist interviews as timed online assessments followed by behavioral rounds; two report three rounds, and one each mentions a business case or a coding screen. Here is what each stage involved.
$135K
Avg. Base Comp
$163K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe the P&G data scientist interview as a process that leans on timed online assessments and structured behavioral conversations, with technical content appearing later and in different forms. Four accounts, from data scientist and data science intern applicants, mention a timed assessment, including the Peak assessment, number logic tests and, in one case, a visual-memory task where the positions of colored dots had to be remembered. One intern recalled a puzzle that required single digits from 1-9 to make an equation equal 30.
After the assessments, two candidates describe three interview rounds built around behavioral and situational questions. Themes included leadership, working with cross-functional teams, handling ambiguous data and prioritizing under competing deadlines. One data scientist was asked to describe a project that showed leadership. An intern who received an offer also walked through a short business case in one of those interviews, and said the emphasis was on structured thinking rather than coding under pressure.
The technical piece is thinly reported. One data scientist described a final online coding screen on a data science case, judged on problem-solving, code quality and explaining reasoning. Another candidate withdrew during the behavioral stage after concluding the culture was not a fit, so reported outcomes ranged from offers to a withdrawal and a rejection. Practice timed puzzles, and prepare STAR stories drawn from real projects.
Synthesized from 5 candidate reports by our editorial team.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates describe one or two timed online assessments, including the Peak assessment and number logic tests alongside situational questions. One candidate also met a visual-memory task with colored dots, and an intern recalled a digits 1-9 equation puzzle. Several found the format fast-paced, so practice under a clock.
One data scientist reports a phone screen before the assessments that covered projects they were proud of and why they were interested in P&G. Other accounts start directly with the online assessment, so this step may not apply to every applicant. Prepare a short, specific story about a project you led.
Two candidates describe three interviews built on behavioral and situational questions, one of them online with colleagues from the office being applied to. Topics included leadership, cross-functional collaboration, ambiguous data and competing deadlines. Use STAR examples and explain your reasoning step by step.
One intern describes a small business case inside an interview, focused on how they would approach the problem rather than on coding. One data scientist describes a final online coding screen on a data science case that looked at problem-solving and code quality. Talk through your approach and write readable code.
