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Openai·Data Scientist·Technical Phone Screen·Senior

Senior
Apr 2024

Summary

Data Scientist interview at OpenAI focused on event-level data modeling for subscription systems. The core problem was messier than it looked on the surface, mostly because of the re-signup edge cases that trip people up if they're not careful about how they reconstruct state from raw events.

Questions Asked (1)

Q1

Design an event-level schema for subscription data that can accurately reconstruct a user's subscription status on any given date, including cases where a user signs up, cancels, and signs up again.

Data ModelingSystem DesignA/B Testing & Experimentation
Author's notes

I went straight to the obvious schema (user_id, timestamp, event_type, plan_type) and felt good about it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the business requirements and the need for point-in-time accuracy, then propose an event-sourced schema that captures all subscription state changes as immutable events. Explain how to reconstruct status for any date by replaying events up to that date, and discuss handling edge cases like cancellations and re-signups.

Pro tip: Emphasize that using event timestamps and a slowly changing dimension (SCD) Type 2 approach can simplify point-in-time queries, and mention the importance of idempotency and late-arriving data in production systems.

1. Clarify Requirements

Ask about the granularity needed (daily, real-time), data sources, and whether the schema should support analytics or operational use. Confirm that the goal is to reconstruct status for any date, including multiple subscription lifecycles.

2. Design Event Schema

Propose a fact table of subscription events with columns like user_id, event_type (signup, cancel, reactivate), event_timestamp, plan_id, and effective_date. Ensure each event is immutable and has a unique event_id.

3. Define Status Reconstruction Logic

Explain how to derive status for a given date by selecting the latest event per user before that date. For example, if the latest event is 'cancel', status is inactive; if 'signup' or 'reactivate', status is active.

4. Handle Edge Cases

Discuss handling of cancellations with future effective dates, backdated events, and multiple signups. Suggest using effective_date to determine when the event takes effect, and consider a status history table for performance.

5. Optimize for Query Performance

Mention building a daily snapshot table or using window functions to precompute status, and indexing on user_id and event_timestamp. Discuss trade-offs between storage and query speed.

Key Points to Mention

  • Event sourcing and immutable event log
  • Point-in-time correctness using event timestamps and effective dates
  • Handling multiple subscription lifecycles (signup, cancel, re-signup)
  • Slowly changing dimensions (SCD) Type 2 for status history
  • Idempotency and late-arriving data
  • Query optimization with snapshots or window functions

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