Data Science Interview Practice
Practise statistics, ML, SQL and case questions with structured feedback on your answers
A taste of a lesson
Mock question please: daily active users dropped 10 percent yesterday. How would you investigate?
Good one. Here is a strong structure; then you try one yourself. First, confirm it is real: check tracking, logging changes and data pipeline delays. Second, segment: platform, app version, country, new versus returning users. A drop concentrated in one segment points to a cause. Third, check internal changes: releases, experiments, outages, marketing. Fourth, external factors: holidays, competitor events, app store issues. Close by saying what you would report and to whom. Your turn: how would you investigate if signups doubled overnight?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Answer technical questions with a clear clarify, approach, trade offs structure
- Explain core statistics and machine learning concepts precisely
- Work through experiment design and metric diagnosis cases
- Identify knowledge gaps and build a revision plan
- Handle questions you cannot fully answer with honesty and method
Lesson plan
- 1 Mapping the interview Identify question types for your target roles and set priorities. Start
- 2 A structure for any answer Use a consistent structure that shows clear thinking. Start
- 3 Statistics and experiments Practise core statistics and A/B test design questions. Start
- 4 Machine learning concepts Answer ML concept questions accurately and concisely. Start
- 5 Cases and SQL reasoning Work through metric drops, product cases and SQL logic. Start
- 6 Projects and revision plan Present your own work well and plan remaining practice. Start
Try asking
About this tutor
A practice tutor for anyone preparing for data science, analytics or machine learning interviews, from first job seekers to experienced people changing roles. You will run mock questions on statistics, machine learning concepts, experiment design, SQL reasoning and product cases, answer out loud in writing, and get specific feedback on correctness, structure and clarity. The tutor teaches a simple answer structure, helps you find and fill knowledge gaps and builds a revision plan around your target roles. It cannot promise any outcome, but it can make your practice deliberate.
Reviews
4.3
3 ratingsSample
- Omar B.Sample
Good mix of stats, ML and SQL questions. I liked that it never pretended practice guarantees anything.
- Jia H.Sample
The feedback on my answers was specific and sometimes uncomfortable, which is exactly what I needed. My structure for case questions is much tighter now.
- Sakura I.Sample
Helped me spot gaps in experiment design. Would like more SQL practice problems, but the reasoning approach helped.
About the teacher
Experiments, causal questions and responsible models, explained for decision makers
9 tutors 437 lessons taught Sample
I help analysts and product people answer the question behind most data work: did this change cause that result? I teach A/B testing, experiment design and the basics of causal inference, plus the responsible side of modelling: fairness checks and explaining predictions. My background is in product analytics and experimentation, where I learned that a clear sentence to a decision...
See Kojo's profile and tutorsMore like this
Other tutors on the same or nearby topics.