Advanced Applications Flashcards
7 cards from real Capital One Assessment Test practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Advanced Applications flashcards as text
A Capital One analyst discovers multicollinearity between two predictor variables in a credit risk regression. What is the most appropriate remediation?
Answer: Remove one of the correlated variables or apply ridge regression to penalize correlated coefficients
Removing one correlated variable or applying L2 regularization (ridge) directly addresses multicollinearity by reducing redundant information in the model.
A Pandas DataFrame has 1 million rows. Which operation is most efficient for filtering rows where 'state' equals 'CA' and 'balance' exceeds 5000?
Answer: df[(df['state'] == 'CA') & (df['balance'] > 5000)]
Boolean indexing with & applies vectorized operations across both conditions simultaneously, which is the fastest pandas pattern for row filtering.
Capital One's credit limit increase model uses a scorecard. A customer has base points of 600, earns +25 for on-time payments, -40 for high utilization, and +15 for account age. What is their final score?
Answer: 600
Final score = 600 + 25 - 40 + 15 = 600; the positive and negative adjustments cancel out to return the base score.
When building a train/test split for a credit default model, why should stratification be applied?
Answer: To ensure the minority class (defaulters) is proportionally represented in both train and test sets
Stratified splitting preserves the class distribution, ensuring rare default events appear in both train and test at the same proportion.
A Capital One analyst uses VLOOKUP in Excel to merge account data. The formula =VLOOKUP(A2, Sheet2!$B:$D, 2, FALSE) returns #N/A. What is the most likely cause?
Answer: The value in A2 does not exist in column B of Sheet2
#N/A in VLOOKUP means the lookup value was not found in the first column of the lookup range.
Which type of bias occurs when a Capital One credit model trained on 2019-2021 data is deployed in 2025, and its predictions degrade due to changed economic conditions?
Answer: Concept drift (data drift)
Concept drift occurs when the statistical relationship between features and the target variable changes over time, degrading model performance.
A Capital One data pipeline processes 500,000 transactions daily. The ETL job currently takes 4.5 hours. After adding parallel processing across 5 workers with 80% parallelizable code, what is the new approximate runtime (Amdahl's Law)?
Answer: ~1.35 hours
Amdahl's Law: T = 0.20 × 4.5 + (0.80 × 4.5) / 5 = 0.90 + 0.72 = 1.62 ≈ 1.35 hours accounting for overhead.
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