Novartis AI Research Scientist interview typically runs 2 rounds: hiring manager phone call, onsite-style day with presentation, group discussions, and 1:1s. It takes about 2 weeks and is paper-driven and rigorous.
$77K
Avg. Base Comp
$97K
Avg. Total Comp
2
Typical Rounds
1-2 weeks
Process Length
Our candidates report that Novartis is looking for more than a polished research story — they want evidence that you can defend your own work at a granular level. In one experience, the interviewers had clearly read the candidate’s first-author paper and expected the discussion to stay anchored in that material, not in broad AI talking points. That pattern suggests the bar is less about name-dropping methods and more about whether you can explain why you made specific choices, what tradeoffs you accepted, and how your prior work maps onto the problem they actually need solved.
A recurring theme is the emphasis on practical scientific judgment. Multiple parts of the process reportedly shifted from technical discussion into questions about procedures a scientist would perform in the role, which tells us they care about whether you can operate in their environment, not just reason abstractly. We also see a strong signal that they value candidates who can connect research experience directly to the position without forcing the fit. The behavioral side appears similarly grounded: one candidate was pressed on a coworker conflict, but even that seemed aimed at understanding how you work inside a cross-functional scientific team. In short, Novartis seems to reward candidates who are precise, credible, and able to translate research into applied impact.
Synthetized from 1 candidates reports by our editorial team.
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Topics based on recent interview experiences.
Featured question at Novartis
What do you tell an interviewer when they ask you what your strengths and weaknesses are?
| Question | |
|---|---|
| 2nd Highest Salary | |
| P-value to a Layman | |
| Hurdles In Data Projects | |
| Valid Anagram | |
| RMS Error | |
| Impute Median | |
| Random Forest Explanation | |
| Greatest Common Denominator | |
| Softmax vs Logistic | |
| Possible Triangles | |
| Unbiased Estimator | |
| Missing Housing Data | |
| Sum to Zero | |
| Flatten JSON | |
| String Palindromes | |
| Overfit Avoidance | |
| Digit Accumulator | |
| Search Linked List | |
| Common Prefix | |
| Data Preparation for Imbalanced Data | |
| K Nearest Entries | |
| Vision Setting and Execution Strategy | |
| Mapping Nicknames | |
| Moving Window | |
| Stakeholder Communication | |
| Why Do You Want to Work With Us | |
| Simple Explanations | |
| Explaining Linear Regression to Different Audiences | |
| Concentric Circles |
Synthesized from candidate reports. Individual experiences may vary.
The process begins with a phone call with the hiring manager. This is mainly an introduction to the project and a discussion of your background, with an emphasis on how your research experience connects to the role.
Before the next round, candidates exchange papers with the team. The interviewers read the candidate’s first-author paper, and the candidate is expected to review background papers for the project so follow-up questions can be grounded in that material.
The second round is a full-day interview with a presentation, group discussions, and multiple 1:1 interviews with scientists and managers. Each panelist interview lasts about 30 minutes and covers technical, scientific, and interpersonal topics, including questions about your resume, research, and how you would perform procedures relevant to the role.