Data Driven Analysis and Optimization Questions

Using data to diagnose problems, prioritize experiments, and drive optimizations. Includes clarifying metrics and goals, identifying and gathering relevant data, analyzing trends and anomalies, forming testable hypotheses, designing experiments such as A B tests, interpreting statistical significance, distinguishing correlation from causation, and recommending actions based on insights. Interviewers look for structured analytic workflows, comfort with basic statistics, and the ability to translate analysis into measurable product or operational improvements.