Data Scientist applicants have rated the interview process at Rakuten with 2.8 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 31% positive. To compare, the company-average is 44.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 32 days to get hired, when considering 26 user submitted interviews for this role. To compare, the hiring process at Rakuten overall takes an average of 35 days.
Common stages of the interview process at Rakuten as a Data Scientist according to 26 Glassdoor interviews include:
One on one interview: 29%
Phone interview: 23%
Skills test: 16%
Presentation: 13%
Group panel interview: 6%
Background check: 6%
IQ intelligence test: 3%
Drug test: 3%
Here are the most commonly searched roles for interview reports -
I applied through college or university. I interviewed at Rakuten (Boston, MA) in Sep 2018
Interview
I met with a recruiter at my school's career fair. He gave me a take-home problem set with three questions to solve in three days and email back to them. Even though I was applying for a data scientist role, the questions were very CS-heavy. In particular, the first question involves writing a function that finds the minimum spanning tree of a directed graph. If you look this up, you'll see that the algorithm for this is quite elaborate and basically impossible to come up with by yourself, especially if you're a data scientist not a software engineer. Nevertheless, I answered all three questions to the best of my ability and emailed my solution and resume back to them. Then it was radio silence for a month. No one even acknowledged that they received my solution, which took me three days to write up because the problems are by no means trivial. I emailed them again to follow up. Still nothing. It was a huge waste of time.
Interview questions [1]
Question 1
Write a function that finds the MST of a directed graph.
this interview process had 5 rounds
2 was a tech test
３ were conversational in nature
with various managers from direct and indirect to the department manager mostly in Japan but also outside Japan.
1st Interview was simple leetcode task and some questions about Kubernetes. 2nd interview - classical ML and DL questions, Final interview is mostly informal, but there may appear some questions about specific experience and problem solving
Interview questions [1]
Question 1
What is the difference between random forest and boosting?
Initial LeetCode coding test, hiring manager interview for profile and role fit, multiple technical rounds covering statistics, machine learning, SQL, Python, and case studies, concluding with behavioral interviews evaluating teamwork, communication, and cultural alignment.