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🚨 Capital One 2025 Data Science OA Questions Leaked! Why Did Seemingly Simple CSV Processing Fail So Many?

2026-01-11

Capital One (C1)'s Data Science interviews have always been renowned for "full-stack capability assessment".

Recently, Capital One released the 2025 October batch OA (Online Assessment). Many students opened the questions and thought: 4 questions, all CSV processing? Seems easy!

The result after submission? Case pass rates were disastrous.

Our oavoservice team worked overnight to deconstruct this CodeSignal question set and discovered countless Data Engineering and ML Pipeline pitfalls buried within.

Today we'll review this "hellish" DS assessment.

🔍 Question Analysis: Full Pipeline Assessment from Cleaning to Modeling

This OA consists of 4 interconnected parts, simulating a real-world industrial data science project: data warehouse extraction -> feature engineering -> data cleaning -> model training.

1️⃣ Question 1: Distributed File Reading and Basic Aggregation

Task: Read drivers.csv and scattered rides_{1-4}.csv files, calculate driver ratings, bilingual ratios, and order success rates.

💣 Hidden Pitfalls:

Multi-file Merging: The problem deliberately splits rides data into 4 files. Many students are used to pd.read_csv('file.csv') but don't know how to efficiently handle batch reading and merging (Concat) of rides_*.csv.

Precision Trap: The problem explicitly requires results to retain two decimal places. In Python, floating-point arithmetic precision loss often causes Hidden Cases to fail.

2️⃣ Question 2: Complex Feature Engineering

Task: Join drivers, rides, cars three tables, calculate driver's "car age", "days since last inspection", "years of experience" and various upvote counts.

💣 Hidden Pitfalls:

SQL Logic in Python: This is essentially a Python version of an SQL problem. You need to master various join methods of pd.merge (Left vs Inner).

Time Travel: The problem provides a virtual "Today" (April 15th, 2023). When calculating days_since_inspection, you must strictly base it on this date. Using datetime.now() directly will fail.

3️⃣ Question 3: Strict Anti-leakage Data Preprocessing

Task: Fill missing values, Ordinal Encoding, Standard Scaling.

💣 Fatal Move - Data Leakage:

This is where most people fail:

Encoding Mapping: The problem requires specific Mapping logic (like "Honda Accord" -> 0). Random encoding order causes test failures.

4️⃣ Question 4: Extremely Imbalanced Classification Model

Task: Train a classifier to predict driver_class (A vs B), requiring Maximize Recall while keeping Precision high.

💣 Hidden Pitfalls:

💡 Why Do You Think You Got It Right But Score Low?

Capital One's OA doesn't just test "whether your code runs", it tests:

Engineering Standards: Is your ETL pipeline robust?

Methodology: Do you understand Data Leakage? Do you understand Metric Trade-offs?

Detail Control: Do your decimal places and encoding order strictly follow documentation?

In the CodeSignal environment, any detail oversight leads to widespread Test Case failures.

🚀 oavoservice: Your Full-Stack Interview Support Expert

Facing Capital One's high workload, pitfall-dense OA, you need not just answers, but professional SRE/Data team support.

oavoservice specializes in providing top-tier written test/interview assistance services for North American students:

CodeSignal Perfect Score Ghostwriting: We're familiar with all C1 question bank variants. Whether Data Cleaning or ML Modeling, we can write perfect code that meets industry standards

Real-time Algorithm/DS Interview Assistance: Stuck on Hard problems? Don't know how to tune metrics? We provide real-time support

Safe, Discreet, Efficient: Years of service experience ensuring 0-risk success

Don't let this 8-second Time Limit block your path to a $150k Offer.

📩 Contact us for any needs.

We consistently provide professional online assessment services for major tech companies like TikTok, Google, and Amazon, guaranteeing perfect scores.

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Secure your Capital One interview opportunity!