OpenAI Data Scientist Interview Questions

800+ verified questions, indexed by team and level. Real questions submitted by candidates who completed OpenAI loops in the last 24 months.

About the OpenAI Data Scientist hiring loop

OpenAI rounds are heavy on ML system design (training infra, inference at scale, RLHF pipelines) and deep technical depth in your specialty. Behavioural rounds probe research-product collaboration. Bar is unusually high; rejection rate ~98%.

Data Science rounds score on statistical rigour, metric definition quality, SQL fluency, framework clarity for case studies, and communication of uncertainty. Companies weight experimental design vs ML modelling differently.

Topics covered in OpenAI Data Scientist interviews

  • 01Probability + statistics (hypothesis tests, A/B testing, p-values)
  • 02SQL fluency under time pressure
  • 03Machine learning fundamentals (bias-variance, regularisation, evaluation metrics)
  • 04Experimental design (sample size, power, interference)
  • 05Analytical case studies with metric definition
  • 06Stakeholder communication of statistical results

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