For hiring teams
Interview data and machine learning candidates with one link
Create an interview link for a data and machine learning role and send it to your candidates. They talk with an AI interviewer about their real work, on their own time. You read the transcript and scores that quote their own words, and your team makes the decision.
Free to start while Aethel is in early access. No card needed.
How it works
How to interview data and machine learning candidates with a link
- Step 1
Create a link for the role
Add the role title, choose Data and machine learning as the field, and set the level. If you want, add a specialty, focus areas, and up to three questions the interviewer must ask word for word.
- Step 2
Send it to your candidates
Share the link however you already reach candidates. Aethel does not message them for you.
- Step 3
Candidates interview on their own time
The interview takes about 15 minutes. Candidates are told up front that the interviewer is an AI, and they agree to share the result with your company before they start.
- Step 4
Review and decide
Read each transcript and the scores, with the quotes behind them. Mark each candidate Advance, Not a fit, or Undecided, and keep private notes.
The interview
What the interviewer covers
It asks about real data and machine learning work and follows up on each candidate's answers. It draws on these topics and picks what fits the role.
- 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
Focus areas on your link steer it further, for example toward a tool, a regulation or a type of client.
Your questions
Sample must-ask questions
Each link can carry up to three must-ask questions. The interviewer asks each one as written. Here are examples for this field.
- Tell me about an analysis or model that someone acted on. How did you check it was right before they did?
- Describe a time the data was wrong or incomplete. How did you find out, and what did you do?
- How do you explain a result with real uncertainty to someone who wants a single number?
Results
What you see for each candidate
A result you can check for yourself. Every score points to what the candidate actually said.
The full transcript
Every question and every answer, in order.
“Not enough evidence” instead of a guess
If the interview did not cover an area, the result says so. It is never shown as a low score. The overall score uses only the areas with evidence.
Your decision and private notes
Track where each candidate stands. Candidates never see your notes.
Four scored areas for data and machine learning
Each is scored from 1 to 100, with the exact quotes behind it.
- Problem solving
- 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
- 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
- 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
- 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.
What Aethel does not do
- Recommend who to hire or guess at seniority.
- Score faces, voices, accents, backgrounds or video.
- Screen anyone out. Everyone who finishes your interview appears in your list.
- Verify degrees, licenses or work history.
Details are on how Aethel uses AI.
FAQ
Questions about interviewing for data and machine learning
Can we interview for a specific role in this field?
Yes. Choose Data and machine learning as the field for the link and add the specialty, such as data scientist or data analyst. Focus areas and must-ask questions steer the interview further.
Can the interviewer ask our own questions?
Yes. You can add up to three must-ask questions to each link, and the interviewer asks each one as written. It picks the other questions from the role, the field and the candidate's answers.
How are candidates in this field scored?
An AI review reads the transcript and scores four areas for this field: Problem solving, Modeling and analysis, Communication, and Collaboration. Each area gets a score from 1 to 100 only when the review can quote the candidate's own words, and every quote is checked against the transcript. Otherwise the area shows "Not enough evidence". The overall score is the average of the areas that have evidence.
Does Aethel check licenses, degrees or work history?
No. Aethel does not verify degrees, licenses, certifications or employment history. Check those the way you do today.
Does Aethel decide who to hire?
No. Aethel does not recommend who to hire, guess at seniority, or screen anyone out. Every candidate who completes your interview appears in your list, and your team makes every decision.
Will Aethel contact our candidates?
No. You send the link and follow up with candidates yourself. Aethel does not message candidates on your behalf.
What do candidates need?
Your link, a free Aethel account, and about 15 minutes. They can type or speak their answers. A camera is not required.
What does it cost?
While Aethel is in early access, you can create an employer account and keep one interview link open at a time for free. Monthly plans are listed on the pricing page. Experts never pay.
Plans are on the pricing page.
Send your first data and machine learning interview link
Create an employer account, describe the role, and copy your link. It takes a few minutes.
Want to show candidates what to expect? What the interview covers for data scientists, analysts and ML engineers