Case studies, A/B test reasoning, ML system design, technical depth probes.
Data Science interviews split across case studies, technical depth (statistics and ML), A/B test reasoning, and ML system design. The conversational rounds are where most candidates underperform: clean structure, calibrated confidence, and explicit assumptions matter more than knowing the latest model.
Each interview here is a 20 to 30 minute live conversation modelled on real DS interview patterns. The interviewer probes for assumption surfacing, baseline comparison, and quantified tradeoffs. After your session, the scorecard separates statistical reasoning from product reasoning so you know which side of the role gap is wider.