I applied in-person. The process took 5 weeks. I interviewed at Revolut (London, England) in Feb 2020
Interview
The interview process took slightly more than 5 weeks. Divided into 4 main stages, the process is extremely efficient thanks to the DS talent team. At each single stage, thorough feedback was provided.
The four stages consist of:
- Phone interview with talent lead (general questions about yourself and some preliminary technical questions around Python, SQL)
- Take home data challenge (quite long to finish but extremely interesting). One week time is available for the candidate to complete it
- Technical interview with 2 senior data scientists. Here you are asked to present findings of the data challenge, answer technical questions on DS or machine learning, do a live python coding exercise
- Final interview with head of team or pm: this is mainly a culture fit assessment as well as previous background and experience check to make sure team's goals and candidate skills are aligned.
Interview questions [3]
Question 1
Questions around Bayesian methods used in data science
The interview process was straightforward and well organized. It started with a recruiter screening about my background and interest in the role, followed by a technical interview covering SQL, Python, statistics, and machine learning concepts. There was also a case study discussion where I explained my approach to analyzing data and communicating insights. Overall, the process was average in difficulty and focused on practical data science skills.
too long process. many steps. strange livecoding where after an optimal solution they ask you about another optimal solution. A little annoying ML interview where you have to solve basic theory of probability tasks for senior position
Rapid-fire format — interviewer moved through topics quickly, frequently interrupting to redirect when answers got too long or off-track. Several questions were skipped due to time pressure or when the candidate struggled to formulate a clear answer
