Compute Customer Spend and Engineer Features for 2023

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Onsite rounds at Capital One.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Capital One during technical interviews.

Question

transactions

+-----------+-------------+--------+------------+--------------+
| tran_id   | customer_id | amount | tran_date  | merchant_cat |
+-----------+-------------+--------+------------+--------------+
| 1001      | 501         | 45.67  | 2023-01-12 | GROCERIES    |
| 1002      | 502         | 120.00 | 2023-01-13 | TRAVEL       |
| 1003      | 501         | 13.50  | 2023-01-14 | DINING       |
| 1004      | 503         | 250.00 | 2023-01-14 | ELECTRONICS  |
+-----------+-------------+--------+------------+--------------+

##### Scenario

Capital One Data Science Manager interview – take-home data challenge using historical credit-card transactions.

##### Question

Write SQL to compute each customer's total and average monthly spend for 2023. In Python, engineer features summarizing spend by merchant category and prepare a modeling dataset.

##### Hints

Think window functions, GROUP BY month, and pivot/one-hot in pandas.

PracHub · Accepted Answer

This question evaluates proficiency in SQL-based temporal aggregation and Python feature engineering on transactional datasets, including computing monthly spend summaries and engineering category-level spending features.

Quick Overview

Compute Customer Spend and Engineer Features for 2023