Ifooddecisionsciences AI Research Scientist interview typically runs 3 rounds: RH, case técnico com gerentes da área, e entrevista com a liderança. O processo levou cerca de 1 mês e foi descrito como pouco claro e inconsistente.
$123K
Avg. Base Comp
$169K
Avg. Total Comp
3-4
Typical Rounds
2-4 weeks
Process Length
Our candidates report a process that feels less like a structured evaluation and more like a moving target. The strongest signal here is not a hidden technical bar, but internal inconsistency: one candidate described expectations that seemed to shift from one conversation to the next, with little alignment between the people involved. That kind of drift usually means the team is still defining the role, and candidates who do best are the ones who can quickly infer what matters from vague prompts and still anchor their answers in concrete outcomes.
A recurring theme is the lack of context around the technical case. The candidate said the objectives were never made clear, which made it hard to know what success looked like. We’ve also seen the same pattern in the manager conversation: questions were broad, generic, and only lightly tied to the actual work, with the most specific prompt being how success is measured. That tells us this company may care more about whether you can impose structure on ambiguity than about any single polished framework.
The final impression matters here, and not just for technical reasons. The candidate noted that leadership asked questions without context and even veered into personal territory in a way that felt insensitive. That suggests the interviewers may be testing judgment and presence as much as research depth, but without much finesse. For our candidates, the real make-or-break factor is showing they can stay composed and precise when the process itself is messy.
Synthesized from 1 candidate report by our editorial team.
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Real interview reports from people who went through the Ifooddecisionsciences process.
I was approached via LinkedIn to take part in the selection process, and right from the start the feeling was one of little clarity about what the position really required. The process had a conversation with HR, then a technical case with the area's managers and, finally, an interview with leadership. The problem is that, throughout the stages, expectations seemed to change or at least were not well aligned among the people involved. Instead of coming away with a clearer view of the role, I ended up with more doubts than at the start.
The technical case was especially frustrating because they did not leave clear evaluation objectives, so it was hard to understand exactly what they were looking for. In the interview with the managers, the questions were very generic and without much context, which made the conversation not very productive. The most concrete question they asked me was about how I measured success, but even that came in a very open way, without a strong connection to the day-to-day of the position. In the final stage with leadership, besides questions without context, they also got into personal topics that had no relation to the job. The most negative point was how a personal and delicate subject was handled, in a very insensitive and superficial way. In the end, the general impression was of a disorganized process, with little empathy and little internal consistency about what they expected from the candidate. I did not receive an offer.
Prep tip from this candidate
It is worth arriving prepared to answer with concrete examples of how you measure success in your work, because that was the only more specific question that came up. It also helps to be ready for a technical case with unclear criteria and for generic questions in the conversation with managers and leadership.
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Topics based on recent interview experiences.
Featured question at Ifooddecisionsciences
Search for a value in log(n) over a sorted array that has been shifted.
| Question | |
|---|---|
| 2nd Highest Salary | |
| Experiment Validity | |
| Merge Sorted Lists | |
| Bagging vs Boosting | |
| First to Six | |
| Employee Salaries (ETL Error) | |
| Scrambled Tickets | |
| P-value to a Layman | |
| 500 Cards | |
| Raining in Seattle | |
| String Shift | |
| Hurdles In Data Projects | |
| N-gram Dictionary | |
| Compute Deviation | |
| Lazy Raters | |
| Button AB Test | |
| Nearest Common Ancestor | |
| Weekly Aggregation | |
| Job Recommendation | |
| Friendship Timeline | |
| Minimum Change | |
| Impression Reach | |
| RMS Error | |
| Bank Fraud Model | |
| Jars and Coins | |
| Find the First Non-Repeating Character in a String | |
| Network Experiment Design | |
| Variable Error | |
| The Brackets Problem |
Synthesized from candidate reports. Individual experiences may vary.
The candidate was first approached via LinkedIn to join the hiring process. At this stage, the role itself was still not very clearly defined, and the candidate felt there was limited clarity about what the position actually required.
The process began with a conversation with HR. This stage appears to have been an introductory screening, but the candidate noted that expectations were not well aligned across the process and the role requirements were still somewhat unclear.
The candidate completed a technical case with managers from the team. The case was frustrating because the evaluation criteria were not made clear, and the questions felt generic and lacking context, making it difficult to understand what the interviewers were looking for.
The final stage was an interview with leadership. In addition to broad, context-light questions, the conversation also included personal topics that were not related to the role, and the candidate felt one sensitive personal subject was handled insensitively.
