Rakuten Data Scientist interview questions

Round 1. Record 5 answer to standard interview questions and complete one Codility test with two tasks. The video interview was a nice feature as it could be fit into your schedule as desired. This reduces scheduling issues, particularly when there is a time difference. Round 2. Complete a presentation, provide a reference letter, and complete two more Codility tasks. Do not bother with the presentation or reference letter until after you do the Codility tests. If you fail the Codility tests and your application will automatically be rejected, then you will feel like an idiot for wasting time on a presentation and wasting someone else's time on the reference letter. Rakuten should split this stage into two: Codilty test then, if successful, presentation and reference letter. While I understand the need for the first round Codility test, where both tasks were simple enough to be FizzBuzz tests and hence act as a quick filter, the second round Codility test was a debugging problem and a geometry problem (calculate the overlap area of two intersecting circles). The particular issue with the geometry problem is that it doesn't test coding ability. It tests your willingness to break the honour code and Google the correct answer. Or it penalises the test-taker for not being fresh out of a computer science course where I guess they would be expected to know the answer? The debugging tasks, heavy focus on Big O metrics and lack of alignment to the applied for job does make me worry that the Rakuten definition of a data scientist is closer to that of a data engineer or more standard computer programmer. Perhaps I dodged a bullet there?

The interview process was great overall. I had a first an interview on Hangouts with a Recruiting Manager at Viki (Ebates' sister company) in which he explained me in great deatail their plans for me, particularly in terms of visa sponsorship and different teams in which I could possibly fit. Around a week after that I had another Hangouts interview with the Head of Analytics in which I summarized my background and work experience and then he explained me some of the analytics challenges they face at Ebates and asked me questions about how I would approached them, (e.g. machine learning solutions to adress business inteligence problems) and general business intellignece questions. The interview was really interesting overall and detailed feedback was given about their final decision.