AI mock interview
Data analyst mock interview
A data analyst mock interview on Mentari is a 20- or 40-minute voice or text interview built from your résumé, the job description and research on the company you are applying to. The AI interviewer asks how you would define and investigate a metric, has you reason through SQL and analysis choices aloud, questions the numbers on your résumé, and returns a scorecard where each of six competency scores is tied to a quote from your answers.
Who this is for
Students and freshers targeting analyst roles, and working professionals moving into analytics from engineering, operations or finance.
What a data analyst interview tests — and how Mentari runs each part
| Round | What it tests | What Mentari does |
|---|---|---|
| Résumé and projects | Whether your analysis projects had a question, a method and a result | Asks what decision your analysis changed, and how you know |
| SQL and data reasoning | Joins, aggregation, window logic — and knowing when a result is wrong | Has you talk through a query approach, then introduces duplicates or nulls |
| Metrics and product sense | Defining a metric, and diagnosing why it moved | Gives you a metric that dropped and follows your investigation step by step |
| Statistics | Sampling, significance, correlation versus causation in plain words | Asks you to explain a result to a manager who does not know statistics |
| Behavioural | Communicating findings, handling pushback from stakeholders | Plays the sceptical stakeholder |
You do not pick these from a menu. Mentari plans the round from your résumé, the job description and what it finds about how the company interviews for the role, so the mix changes with every session.
Typical questions — and the follow-up that comes next
Lists of interview questions are everywhere. What decides the interview is the second question: the one that checks whether the first answer was real. These are typical of the role, each paired with the follow-up a good interviewer asks.
01Daily active users dropped 8% this week. How do you investigate?
Follow-up · You have found it is only on Android. What is the next cut, and what would make you stop digging?
02How would you find duplicate customer records in a table?
Follow-up · Two rows differ only in the case of the email address. Are they duplicates, and who decides?
03What is the difference between a LEFT JOIN and an INNER JOIN?
Follow-up · Tell me about a time the wrong join silently changed a number you reported.
04Walk me through an analysis on your résumé.
Follow-up · What decision was made differently because of it?
05How would you measure whether a new feature is successful?
Follow-up · The metric went up but revenue did not. What do you tell the product manager?
06Explain a p-value to someone who is not technical.
Follow-up · They now ask, "so is it true or not?" What do you say?
07Which chart would you use to show this, and why?
Follow-up · What would a misleading version of the same chart look like?
08Your dashboard and the finance team’s number disagree. What do you do?
Follow-up · It turns out yours is the wrong one. How do you handle that?
Where candidates lose marks
- Jumping to a query before asking what the business question is.
- Listing tools (Excel, SQL, Power BI, Python) instead of describing a result.
- Treating every correlation on a dashboard as a cause.
- Giving an investigation plan with no stopping point.
What your scorecard shows
About thirty seconds after you finish, you get a score out of 10 and six competency scores. Each one is tied to a verbatim quote from your transcript, so you can see the exact answer that earned or cost the marks. How scoring works.
| Competency | What it measures |
|---|---|
| Communication | Whether your answers were clear, direct and easy to follow — not your accent. |
| Technical depth | How well you understand the substance of the role, beyond definitions. |
| Problem solving | How you break down an unfamiliar problem and reason towards an answer. |
| Ownership | What you personally did, decided and were accountable for. |
| Structure | Whether your answers had a shape: context, action, result, and a point. |
| Company fit | Whether you showed the signals this particular company looks for in this role. |
Practise for another role
Last updated · Written by the Mentari team