Data Problem Solving and Business Context Questions
Practical data oriented problem solving that connects business questions to correct, robust analyses. Includes translating business questions into queries and metric definitions, designing SQL or query logic for edge cases, handling data quality issues such as nulls duplicates and inconsistent dates, validating assumptions, and producing metrics like retention and churn. Emphasizes building queries and pipelines that are resilient to real world data issues, thinking through measurement definitions, and linking data findings to business implications and possible next steps.
MediumTechnical
0 practiced
Two analytics tools show different monthly revenue numbers (Tool A: 1.02M, Tool B: 980k). Provide a reconciliation plan: datasets and dimensions to compare, instrumentation and sampling checks, timezone and attribution window differences, and how to present root causes to the business.
MediumTechnical
0 practiced
Refund rate jumped 4x overnight. Outline an investigation plan: aggregate checks and drilldowns you would run first, how to determine if this is an instrumentation issue versus product issue, and how to prioritize fixes and communicate to stakeholders.
MediumTechnical
0 practiced
Explain how to compute weekly active users (WAU) where weeks start on Monday in the user's local timezone. Provide sample SQL logic for converting UTC timestamps to local week buckets, note performance concerns, and describe validation strategies across DST transitions.
HardTechnical
0 practiced
You suspect bot-driven fake signups are inflating DAU. Propose a combined SQL and ML approach to detect and remove fraudulent events. Include feature ideas, labeling strategies (rule-based and human review), thresholding and calibration, and how to measure tradeoffs between false positives and business loss.
MediumTechnical
0 practiced
You have a churn probability model that outputs p_churn for each user. Describe how to translate model outputs into business actions: choosing thresholds, building treatment cohorts, estimating expected lift, calibration checks, and how to measure campaign impact after deployment.
Unlock Full Question Bank
Get access to hundreds of Data Problem Solving and Business Context interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.