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This question evaluates data manipulation and aggregation competencies using SQL or Python, with emphasis on demographic segmentation and time-based summarization of paid claim amounts.

  • Medium
  • CVS Health
  • Data Manipulation (SQL/Python)
  • Data Scientist

Calculate Medical Claims by Age and Gender in 2024

Company: CVS Health

Role: Data Scientist

Category: Data Manipulation (SQL/Python)

Difficulty: Medium

Interview Round: Technical Screen

MEMBERSHIP +----+----------+--------+---------+ | id | age_band | gender | zipcode | +----+----------+--------+---------+ | 1 | 18-25 | F | 90001 | | 2 | 26-35 | M | 10001 | | 3 | 18-25 | M | 02139 | | 4 | 36-45 | F | 60616 | | 5 | 26-35 | F | 94105 | +----+----------+--------+---------+ ​ CLAIM +----+------------+-----------+-------------+ | id | claim_date | paid_amt | insurance | +----+------------+-----------+-------------+ | 1 | 2024-03-15 | 550.00 | PPO | | 1 | 2023-11-20 | 200.00 | HMO | | 2 | 2024-01-05 | 1300.00 | HMO | | 3 | 2024-07-23 | 75.00 | PPO | | 4 | 2022-12-31 | 800.00 | PPO | +----+------------+-----------+-------------+ ##### Scenario Health-insurance analytics team wants to understand how much was paid for medical claims by specific demographic segments. ##### Question Calculate the total paid_amt in 2024 for members in a given age_band and gender. 2. For a given age_band, show the yearly trend of total paid_amt across all available years. ##### Hints JOIN membership and claim on id, filter dates, GROUP BY or use WINDOW functions for yearly totals.

Quick Answer: This question evaluates data manipulation and aggregation competencies using SQL or Python, with emphasis on demographic segmentation and time-based summarization of paid claim amounts.

Last updated: Mar 29, 2026

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