## Problem You are asked to build a CTR (click-through rate) prediction model for a content recommendation system. Walk through the full ML modeling process: **1. Problem framing** - Binary classification: will user click on item? (positive = click) - Training signal: implicit feedback (clicks), with heavy class imbalance (~1% CTR) **2. Feature engineering** - User features: historical CTR, session recency, demographics - Item features: category, age, historical CTR - Context features: device, time-of-day, position bias **3. Model options** - Logistic Regression (baseline, interpretable) - Gradient Boosted Trees (GBDT) for tabular features - Deep factorization machines or two-tower neural model for large sparse IDs **4. Evaluation** - Metrics: AUC-ROC, log-loss, calibration - Why accuracy is a poor metric at 1% CTR ## Follow-ups 1. How do you handle position bias in training data (items shown higher get more clicks)? 2. How do you evaluate the model offline before an A/B test? 3. The model's calibration drifts after 2 weeks — what causes this and how do you fix it?

InterviewDB Experience

ML Modeling: Design and Evaluate a Click-Through Rate Prediction Model

phone

Interview Experience

Problem You are asked to build a CTR (click-through rate) prediction model for a content recommendation system. Walk through the full ML modeling process: 1. Problem framing Binary classification: will user click on item? (positive = click) Training signal: implicit feedback (clicks), with heavy class imbalance (~1% CTR) 2. Feature engineering User features: historical CTR, session recency, demographics Item features: category, age, historical CTR Context features: device, time-of-day, position…

Full Details

🔒

Unlock all Reddit questions

Full insider details, leaked discussions, and candidate experiences.

or every company, $100/year →

About This Question

This is a candidate experience report from a reddit interview during the phone round.

It covers the following topics: Coding, Mle, Phone .

Topics

Coding Mle Phone

ML Modeling: Design and Evaluate a Click-Through Rate Prediction Model

Interview Experience

Full Details

About This Question

Topics

More Reddit Interview Questions