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TikTok·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

TikTok data scientist interview with a SQL-heavy technical screen. The question was applied and scenario-based, not just 'write a join', which I appreciated but also didn't fully expect.

Questions Asked (1)

Q1

Given a page_views table and a purchases table for an e-commerce platform, write a SQL query that returns, for each month: the number of distinct visitors, the number of distinct purchasers, and the conversion rate. Then extend it to also include average order value per month.

Product Analytics & MetricsData Modeling
Author's notes

The core join wasn't bad but I tripped on the conversion rate piece.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schemas and definitions (e.g., what counts as a visitor, purchaser, and conversion rate). Then write a SQL query that aggregates page views and purchases separately by month, joins them on month, and computes the metrics. Finally, extend the query to include average order value by summing purchase amounts and dividing by distinct purchasers.

Pro tip: Always clarify ambiguous terms like 'visitor' (unique user vs. session) and 'conversion rate' (purchasers/visitors vs. purchases/visitors) before writing SQL—this shows you think like a data scientist, not just a coder.

1. Clarify definitions and assumptions

Ask clarifying questions about table schemas, what constitutes a visitor (e.g., distinct user_id), a purchaser (e.g., distinct user_id with a purchase), and how conversion rate is defined. State your assumptions explicitly.

2. Aggregate page views by month

Write a subquery or CTE that groups page_views by month and counts distinct visitors (e.g., COUNT(DISTINCT user_id)).

3. Aggregate purchases by month

Write a subquery or CTE that groups purchases by month and calculates distinct purchasers (COUNT(DISTINCT user_id)) and total revenue (SUM(amount)).

4. Join and compute metrics

Join the two aggregated tables on month, compute conversion rate as distinct purchasers divided by distinct visitors, and average order value as total revenue divided by distinct purchasers. Handle division by zero.

5. Present final query and explain logic

Show the complete SQL query, explain each part, and discuss any edge cases (e.g., months with no purchases, timezone considerations).

Key Points to Mention

  • Use COUNT(DISTINCT ...) for visitors and purchasers to avoid double-counting.
  • Define conversion rate clearly: typically distinct purchasers / distinct visitors.
  • Average order value = total revenue / number of orders (or distinct purchasers if one order per purchaser).
  • Handle months with zero visitors or purchasers to avoid division by zero.
  • Consider timezone or date truncation for monthly grouping (e.g., DATE_TRUNC('month', timestamp)).
  • Use LEFT JOIN to ensure months with page views but no purchases are included.

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