Interview Questions (Data Scientist – Round 1 & 2): Tell me about your background and relevant data science experience How did you evaluate feature importance in your ML models (Random Forest, SHAP)? What evaluation metrics did you use and why? Coding: Write a function to return the first repeating element in a list OOP concepts: inheritance, use of super(), and behavior of shared/class variables ML & Statistics: Difference between mean and median, and when to use each What is standardization and why is it needed? Data imbalance techniques and how they work Case / System Design: Design an email classification system (spam vs normal) What features would you use? Follow-up: handling real-time constraints (latency), model drift, and model selection (LLM vs smaller models)