Data Scientist applicants have rated the interview process at Lucid Software with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 49.2% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 18 days to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at Lucid Software overall takes an average of 22 days.
Common stages of the interview process at Lucid Software as a Data Scientist according to 2 Glassdoor interviews include:
Phone interview: 67%
IQ intelligence test: 33%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 2 weeks. I interviewed at Lucid Software in Sep 2018
Interview
I applied online and was very quickly sent a take-home challenge. I took about 8 hours to finish and I got chance to chat with hiring manager. The questions were standard, but the problem was that they were looking for immediate hires, a criteria that I clearly didn't satisfy from my resume (as I am still a current student and I list my expected graduation date, which is far away from the time I interviewed). I wouldn't have wasted the time if I had known this earlier.
Interview questions [2]
Question 1
Take-home challenge, be careful about class imbalance
I applied online. The process took 3 weeks. I interviewed at Lucid Software (Salt Lake City, UT) in Nov 2018
Interview
1. Machine Learning take-home assignment that had to be completed in 3-4 days. Recruiter advised completing in about 4 hours. However, it took me about 10 hours to solve it since the data size was huge!
2. Machine Learning / Case Study Interview - Conceptual ML case study questions and some questions from the previous take-home interview.
3. Business / Case Study Interview - A mix of behavioral and business case study questions. Required good communication skills, logical reasoning, and business acumen.
Interview questions [1]
Question 1
How to treat Ordinal variables, Overfitting, Linear Models, Cross Validation etc.