Data and machine learning
AI interviews for data scientists, analysts and ML engineers
Talk through your real data and machine learning work with an AI interviewer. See your results first, with the quotes behind every score, and choose who sees them.
- Free for experts
- About 15 minutes, whenever you like
- Type or speak. No camera needed
Who it's for
For people who work in data and machine learning
Analytics, data science, machine learning and data engineering.
Example roles
- Data scientist
- Data analyst
- Machine learning engineer
- Analytics engineer
- Data engineer
- Applied scientist
- MLOps engineer
When you apply, you can name your exact specialty. The interviewer fits its questions to it.
Not quite your field? See every field
The interview
What the 15-minute interview covers
A conversation about your own work, not trivia. Questions usually start with something you worked on recently, dig into what made it hard, and may end with a realistic situation from your field. Each question follows up on what you said.
Topics the interviewer draws on
- A model or analysis that changed a real decision
- Messy, missing or biased data and how they handled it
- Choosing evaluation metrics and what those metrics missed
- A model or dashboard that broke or drifted after launch
- An experiment or A/B test and how they read the results
- Explaining uncertainty to people who wanted a yes or no answer
- Choosing between a simple approach and a complex one
It picks what fits your specialty. It does not read these out as a list.
How your answers are scored
After the interview, an AI model reads your transcript and looks for evidence in four areas. Each area is scored from 1 to 100 only when it can quote your own words.
Problem solving
Messy data, failures, tradeoffs
Counts as evidence when the candidate describes a specific data or modeling problem, its cause, what they tried, a trade-off, or a measured result.
Modeling and analysis
Methods, metrics, validation
Counts as evidence when the candidate describes how they built or evaluated a model, analysis or data pipeline: data sources, features, methods, metrics, validation, or how they checked the result was right.
Communication
Explaining findings and their limits
Counts as evidence when the candidate describes explaining findings or models to other people: a report, a dashboard, a presentation, or walking stakeholders through results and their limits. Answering clearly is not, by itself, communication evidence.
Collaboration
Stakeholders, engineers, feedback
Counts as evidence when the candidate describes working with other people: stakeholders, engineers, product partners, reviews, mentoring or feedback. Saying "we" is not, by itself, collaboration evidence.
If your answers do not cover an area, it shows Not enough evidence instead of a low score. Scores come only from the words in your transcript. Your face, voice and accent are never scored.
Practice
Three example practice questions
These come from the practice room for data and machine learning. In the real interview, questions follow up on your own answers, so yours will be different.
- Question 1
Tell me about an analysis or model you built that someone actually used, and what it changed.
- Question 2
Imagine your model's accuracy drops sharply a month after launch. What would you check first, and why?
- Question 3
How would you explain the uncertainty in your results to a manager who wants a yes or no answer?
No account needed. Practice answers are not saved.
After the interview
What you get
Your results, first
Read your transcript and your scores in Problem solving, Modeling and analysis, Communication, and Collaboration, with the quotes behind each one. An area without enough evidence says so.
Share links you control
Share your result with a link only when you want to. You decide who gets it, and you can turn the link off at any time.
Company interview links
If a company sends you its own interview link, you see the company and the role, and agree to share that interview with them before you start. You see the same result they see.
Free, with retakes
Experts never pay. You can retake the interview up to 3 times, and your newest result replaces the one before it. If a technical problem cuts an interview short, you can get a free retake.
How data is stored, used and deleted is in our privacy policy.
FAQ
Questions from data scientists, analysts and ML engineers
What will the AI interviewer ask me about?
Your own data and machine learning work. Questions usually start with something you worked on recently and dig into what made it hard. Later questions may give you a realistic situation from your field or a hard choice to make. Each question follows up on what you said. There are no trick puzzles.
How is the interview scored for data and machine learning?
After the interview, an AI model reads your transcript and looks for evidence in four areas: Problem solving, Modeling and analysis, Communication, and Collaboration. An area gets a score from 1 to 100 only when the model can quote your own words for it. Otherwise it says "Not enough evidence" instead of guessing. Your face, voice and accent are never scored.
Do I have to share confidential details?
No. The interviewer is told not to ask for names or confidential details about clients, patients, students or employers, and to let you describe situations without identifying anyone. Describe datasets, models and results without sharing anything proprietary.
I am an analyst, not a machine learning engineer. Is this the right field?
Yes. Data analysts, data scientists, data engineers and machine learning engineers all use this field. Name your exact role as your specialty when you apply, and the questions follow it.
Is this a certification or a license check?
No. An Aethel interview is not a certification, license or credential, and it does not verify degrees or licenses. It is a record of how you talked about your own work in one interview.
Who sees my results?
You see your results first. A company sees an interview only if you took it through that company's interview link. Anyone else sees a result only through a share link or a PDF verification code you make. If you turn on your Find experts profile, anyone can see your name, field, specialty, and area scores, but never your transcript or contact details. You can turn off a share link, a code, or your Find experts profile at any time. You can delete your interview records at any time from your profile page.
Is it free, and can I retake it?
Yes, it is free for experts. You can retake the interview up to 3 times from your results page, and your newest result replaces the one before it. If a technical problem cut an interview short, your results page offers a free retake that does not count toward the 3. If it does not, ask for a review. An interview taken through a company's link is taken once.
Can I practice first?
Yes. The practice room uses sample questions for data and machine learning and saves nothing. You do not need an account to try it.
More detail: how interviews work
Ready when you are
Apply in a few minutes, then interview whenever it suits you. You decide who sees your results.
Hiring data scientists, analysts and ML engineers? See how companies interview for data and machine learning