Databricks · Data Scientist (New Grad)
Databricks' new-grad Data Scientist loop spans four core areas: SQL/data manipulation, applied statistics and A/B testing, machine-learning fundamentals, and a coding round, usually wrapped with a behavioral and a case-style discussion. It is genuinely broad — you're expected to be fluent in querying data, reasoning about experiments, and explaining models from first principles, not just calling a library. Expect to defend your statistical choices out loud.
Practice this interview
Free · a live voice mock calibrated to this exact role
What this interview tests
- SQL fluency (joins, window functions, cohort/funnel queries)
- Applied statistics and A/B test design
- ML fundamentals (bias-variance, regularization, model intuition)
- Choosing the right metric (precision/recall, AUC) for the problem
- Python data manipulation (pandas-style) and light coding
- Product sense and framing an analysis
Common question themes
Write a window-function query for cohort retention
Design an A/B test and explain how you'd read the result
"Explain the bias-variance trade-off"
"How would you handle a heavily imbalanced dataset?"
Pick and justify a success metric for a product change
pandas-style data wrangling / a light algorithm problem
Modeled on a public Databricks new-grad Data Scientist posting