Just finished the Deloitte DS loop. This was for a senior data scientist role in their AI & Data practice. Sharing a breakdown because the prep resources for Deloitte DS specifically are thin.
The format I went through (4 rounds over 3.5 weeks)
Round 1: Recruiter screen Usual Deloitte recruiter questions. Travel, background, why the firm. They mentioned the role would involve client-facing deliverables, not internal product work. If you're coming from a pure product company DS background, that context matters.
Round 2: SQL + analytics challenge (async) Three SQL problems, about 45 minutes. One was a GROUP BY + window function problem, one was a multi-table JOIN with some filtering logic, one was closer to a business question where you had to write SQL to answer "what percentage of clients had a drop in activity month over month."
Not LeetCode hard but you need to be fluent. Window functions (LAG, LEAD, RANK, ROW_NUMBER) showed up. Practice those specifically.
Round 3: Live case + stats interview (60 min) Two-part interview. First half: a case scenario, something like "a client's ML model for credit scoring is underperforming. How do you diagnose and fix it." This is less about code and more about your mental model for model debugging. Talk through: data drift, feature importance, validation methodology, class imbalance.
Second half: statistics concepts. Bias-variance tradeoff, when to use which model, p-value interpretation, A/B testing design. Real questions, not trick questions. Know your stats cold.
Round 4: Behavioral + presentation Presented a slide deck summarizing a past project. 10 minutes, then Q&A. Questions were about methodology decisions, stakeholder communication, how I explained findings to non-technical clients.
What stood out vs typical DS loops The client communication piece is everywhere at Deloitte. Even in the model debugging case, they asked how I'd explain my findings to an executive. If you've only worked in internal-facing DS roles, practice articulating technical results in business terms. That's the gap I see most DS candidates miss here.