Type of Questions to Expect 

• ​Technical Skills (SQL, Python/R, Excel): Questions that test your ability to query databases, manipulate data, and use statistical tools. Example: "Write a SQL query to find the second highest salary in a table."
• ​Analytical & Business Thinking: Questions that require you to define metrics, diagnose a problem using data, or design an experiment. Example: "A product feature was launched, and its usage dropped by 20\% week-over-week. How would you investigate this?"
• ​Behavioral & Communication: Questions about how you work with stakeholders, explain complex results to a non-technical audience, and manage errors or disagreements. Example: "Describe a challenging data set you worked with and how you ensured the data quality."

​What the Interviewer Will Expect

1. ​Demonstrate Problem Framing: Before jumping to a solution, they expect you to clarify the business question and define the necessary data or assumptions.
2. ​Exhibit Technical Proficiency: You should be able to write clean, efficient, and well-commented code (especially SQL) and understand basic statistical concepts.
3. ​Translate Complexity: You must clearly explain your findings and the underlying statistical concepts (like p-values or confidence intervals) in simple terms to executives or non-data colleagues.
4. ​Be Skeptical and Thorough: Show that you think critically about data quality, potential biases, and limitations of the analysis.

​Tips on Getting Ready

• ​Drill SQL: Practice intermediate-to-advanced SQL concepts, including joins, window functions, and subqueries.
• ​Review Statistics Basics: Refresh your understanding of descriptive statistics, A/B testing principles, and common pitfalls (e.g., correlation vs. causation).
• ​Structure Your Analysis: When tackling a business problem, use a framework like A-B-C (Analyze the Situation, Break Down the Problem, Conclude with a Recommendation) to ensure a complete answer.
• ​Prepare Case Studies: Have 3-5 ready-to-share stories about how your data analysis led to a measurable business outcome.