Prepare to dive into a structured interview that mirrors the challenges faced by real-world data scientists and machine learning engineers. In this immersive Movie Recommender Interview, you’ll work through carefully designed questions that test your skills across data wrangling, SQL, exploratory data analysis (EDA), statistics, and machine learning — all within the context of a movie recommendation system.

Across this simulated 60-minute session, you’ll engage with progressive, scenario-based questions that reflect how data science projects unfold in practice. From cleaning and analyzing user–movie datasets to designing recommendation algorithms, each task connects seamlessly to the next, offering a holistic and rigorous preparation journey.

Get ready to sharpen both your theoretical knowledge and coding ability while demonstrating your capacity to extract insights, design models, and communicate results effectively.

• Master end-to-end data workflows in a movie recommender setting.
• Strengthen SQL skills by querying user–movie ratings data.
• Apply Python for data wrangling, EDA, and visualization tasks.
• Explore statistical methods to validate hypotheses on user behavior.
• Practice building and evaluating recommendation algorithms.