Post by Nikhil Naganur

Role- Data Scientist at Google CTC- 30 to 40 LPA Interview Questions 👇 Level-1 → Conceptual & Applied 🔸 How do you choose metrics when false positives cost more than false negatives? 🔸 How do you decide if a feature is numerical, categorical, or ordinal? 🔸 How do you tell correlation from true impact on the target? 🔸 What is data leakage, and how do you prevent it? 🔸 How would you design an A/B test for a new Search feature? Level-2 → Depth + Edge Cases 🔸 Offline metrics improve but business KPIs drop how do you debug? 🔸 Training data is biased toward power users what breaks and how do you fix it? 🔸 How do you handle thousands of features with limited data? 🔸 How do you explain a complex model to non-technical stakeholders? 🔸 An A/B test shows no lift, but leadership believes in the feature next step? Level-3 → Practical Code Based Questions 🔸Write code to handle missing numerical and categorical values, encode features & prepare data for modeling. 🔸With only 3% positive labels, how do you improve recall without hurting precision? 🔸How do you split time-based data without leakage? 🔸Train a tree-based model, extract the top 5 most important features, and explain how you would validate them. 🔸Given events(user_id, event_date), write a SQL query to calculate Day-1 and Day-7 retention. These questions are great to practice but you need more than just skills to crack a data science interview at top tech companies. Switching to top tech giants isn’t easy, but it’s possible if you approach prep with structure, clarity & get mentorship from the correct mentors. That’s why I recommend structured guidance, esp. for data scientist roles & if you find prep hard to manage with a full-time job, check out Data Science program by Bosscoder Academy. 🔗 Explore their Data Science program here → bcalinks.com/9JDhET5 They’ve helped 2200+ professionals transition successfully through: 💡 Structured curriculum covering Advanced Python lib, Maths, ML& Deep Learning, etc. 💡 Industry projects with real world datasets that build your portfolio. 💡 1:1 mentorship from data scientists at top product companies. 💡 100% placement support to help you land your dream data role. #datascientist #growth #collab #pbc