Data Science Team Lead applicants have rated the interview process at Kaizen Gaming with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 50.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Science Team Lead roles take an average of 37 days to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at Kaizen Gaming overall takes an average of 24 days.
Common stages of the interview process at Kaizen Gaming as a Data Science Team Lead according to 2 Glassdoor interviews include:
One on one interview: 50%
Group panel interview: 25%
Skills test: 25%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 2 weeks. I interviewed at Kaizen Gaming in May 2023
Interview
There was an initial screening by the HR team and then one 2-hour technical interview regarding everything around applied data science. After that, there was an additional 1-hour technical interview around MLOps and engineering (incl. live coding and code review) followed by a final interview with HR mostly around Kaizen culture and some team leading-related questions. The overall process was very quick, all people were friendly and there was no take-home exercise which meant there was less time needed to devote in the interview process.
Interview questions [1]
Question 1
Anything on applied data science incl. feature engineering, feature selection, modeling, model tuning, model evaluation.
I applied online. The process took 2 months. I interviewed at Kaizen Gaming in Jan 2025
Interview
I was first contacted by a recruiter and setup a one hour interview. The recruiter knew a lot about the position and was very helpful. We discussed my background, company fit, values, starting date and salary expectations. Unfortunately the company offers rather low salaries for the skillset they are asking for.
After that I had a technical interview. The interview was very well designed and went through a case study about a grad detection system. We explored the problem, talked about stakeholder management but also dove very deep technically.