PayPal·Data Scientist·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

PayPal data scientist interview with a SQL-heavy technical screen. The question was specific and had a few layers to it, more than I expected for what I thought would be a standard analytics round.

Questions Asked (1)

Write a SQL query that uses CASE WHEN to produce conditional aggregates, such as counts of approved vs declined transactions per merchant and the sum of amounts flagged for review. Then explain why CASE WHEN is more portable across SQL dialects than approaches like SUM(column = 'x'), and walk through the readability and maintainability trade-offs.

Technical Trade-offsData ModelingProduct Analytics & Metrics

Author's notes

The query itself wasn't too bad, I got the structure right.

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AI HintsAI Generated

Suggested Approach

Start by writing a clear SQL query that uses CASE WHEN inside aggregate functions to compute conditional counts and sums per merchant. Then explain the portability advantages of CASE WHEN over boolean expressions, and discuss readability and maintainability trade-offs in a team setting.

Pro tip: Mention that CASE WHEN is ANSI SQL standard and works across all major databases, while SUM(column = 'x') relies on implicit boolean-to-integer casting that fails in strict databases like PostgreSQL. Also, highlight that CASE WHEN allows handling NULLs explicitly, which is crucial for accurate conditional aggregates.

1. Write the Query

Construct a SQL query that groups by merchant and uses CASE WHEN inside COUNT and SUM to compute approved/declined counts and sum of amounts flagged for review.

2. Explain Portability

Discuss why CASE WHEN is more portable: it's ANSI SQL, avoids implicit boolean casting, and works consistently across databases like PostgreSQL, MySQL, SQL Server, and Oracle.

3. Analyze Readability

Compare readability: CASE WHEN is more verbose but self-documenting, while SUM(column = 'x') is concise but may confuse those unfamiliar with boolean casting.

4. Discuss Maintainability

Consider maintainability: CASE WHEN makes logic explicit and easier to modify, but can lead to longer queries; boolean expressions are shorter but may break with schema changes or strict SQL modes.

5. Summarize Trade-offs

Conclude with a balanced view: prioritize portability and clarity with CASE WHEN, especially in cross-database environments, but acknowledge that boolean expressions can be acceptable in controlled settings.

Key Points to Mention

ANSI SQL compliance and cross-database compatibility
Implicit boolean-to-integer casting differences (e.g., PostgreSQL vs MySQL)
Explicit NULL handling with CASE WHEN
Readability: self-documenting vs concise but cryptic
Maintainability: ease of modification and debugging
Performance considerations: both approaches typically optimize similarly

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