Meta·Data Scientist·Technical Phone Screen·Intermediate

Intermediate

Sep 2023Remote

Summary

Meta DS interview with a SQL question centered on video call behavior data. The setup was more open-ended than I expected for a phone screen, basically handed two tables and told to figure out how to define 'interest' in a feature that didn't exist yet.

Questions Asked (1)

Given a table of video call logs and a user attributes table, write SQL to identify users who seem interested in group video calls.

Product Analytics & MetricsData Modeling

Author's notes

The tricky part wasn't the SQL itself, it was deciding what 'interest' even means with no ground truth.

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AI HintsAI Generated

Suggested Approach

Start by clarifying what 'interested in group video calls' means—likely users who frequently initiate or participate in calls with 3+ participants. Then write SQL that joins call logs with user attributes, filters for group calls, and aggregates per user to identify those with high group call engagement.

Pro tip: Define a clear threshold for 'interested' (e.g., at least 3 group calls in the last 30 days) and mention that you'd validate it against business goals or user retention metrics. Also, consider segmenting by user attributes to see if interest varies by demographics or platform.

1. Clarify the definition

Ask or state what constitutes a 'group video call' (e.g., 3+ participants) and what 'interested' means (e.g., frequent initiator or participant).

2. Explore the tables

Identify relevant columns in the call logs (call_id, user_id, participant_count, call_time) and user attributes (user_id, demographics, etc.).

3. Filter and aggregate

Filter call logs for group calls, then aggregate per user to count group calls or total duration, applying a threshold to flag interest.

4. Join with user attributes

Join the aggregated results with the user attributes table to enrich the analysis and potentially segment users.

5. Write and validate SQL

Construct the final SQL query, ensuring it handles edge cases (e.g., users with no group calls) and validate results with sample data.

Key Points to Mention

Definition of group call (e.g., participant_count >= 3)
Metric for interest (e.g., count of group calls, total duration, frequency)
Time window (e.g., last 30 days) to capture recent interest
Threshold for 'interested' (e.g., at least 3 group calls)
Handling users with no group calls (LEFT JOIN or filtering)
Segmentation by user attributes (e.g., age, platform) to understand interest drivers

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.