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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Real interview reports from people who went through the Novartis process.
I started with a 30 minute phone call with the hiring manager, and that set the tone for the rest of the process. It was mostly an introduction to the project and a discussion of my background, but they also wanted to understand how I would connect my research experience to the role. After that, I had a much bigger onsite-style day with several scientists and managers. Before the second round, we exchanged papers, so they read my first-author paper and I read some of the background papers for the project, which was actually very helpful because the follow-up questions were clearly grounded in that material.
The second round was a full day interview with a presentation, group discussions, and a series of 1:1s with panelists. Each scientist interview was about 30 minutes, and the questions could shift between technical, scientific, and interpersonal topics. The technical part was described as very technical but straightforward, and one of the main things they seemed to care about was whether I really knew everything on my resume. I was also asked about a procedure that would typically be performed in the role, so it felt less like abstract theory and more like whether I could actually do the work. On the behavioral side, I got a question about a conflict with a coworker and how I handled it, and there was also a broader question about how I would apply my research experience to the position. Overall the process felt rigorous but fair, and the biggest takeaway for me was that preparation should go beyond general interview practice: know your own papers, be ready to explain your research clearly, and be able to connect it directly to the job.
Prep tip from this candidate
Be ready to defend every line on your resume and to discuss your own paper in detail, since the follow-up questions were tied directly to that. Also prepare a clear example of a workplace conflict and a concise explanation of how your research experience maps onto the role.
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Sourced from candidate reports and verified by our team.
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 | |
| Hurdles In Data Projects | |
| P-value to a Layman | |
| Valid Anagram | |
| Fair Coin | |
| RMS Error | |
| Reducing Error Margin | |
| 85% vs 82% | |
| Greatest Common Denominator | |
| Random Forest Explanation | |
| Softmax vs Logistic | |
| Possible Triangles | |
| Unbiased Estimator | |
| Secret Wins | |
| Sum to Zero | |
| Missing Housing Data | |
| 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 | |
| DDoS Attack Response | |
| Mapping Nicknames | |
| Client Solution Pushback | |
| Moving Window |
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.