Meta·Data Scientist·Technical Phone Screen
May 2026
Brutal SQL gauntlet at Meta for a DS role. Four parts, all in one question, covering conversion rates, churn, cancellation CIs, and rolling window comparisons with timezone-aware logic throughout. Felt like a take-home disguised as a live session.
- Given a schema with users (including timezone), app sessions, and orders, write SQL to compute daily conversion rate by city and platform for the last 7 days using user-local dates, where conversion rate is distinct users with at least one completed order that day divided by distinct users with at least one session that day. Days with no data should emit zeroes.
- Flag city-platform pairs where the 7-day average conversion rate dropped by more than 30% compared to the preceding 7-day window, using user-local dates and without double-counting users across platforms.
- Return a list of churned users as of today, defined as users who had at least one completed order in a specified historical window but zero completed orders in a more recent window, using their local timezone. Include their last order local date and days since last order.
- For the last 14 local days, compute cancellation rate by city (cancelled orders divided by all orders) and return the top 3 cities by largest absolute increase versus the prior 14 days. Include 95% Wilson confidence intervals for each period.
“The timezone conversion part is what gets you.” The rest of the author's notes on Data Scientist interview at Meta, Technical Phone Screen round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.
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