Data Scientist applicants have rated the interview process at BILL with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 33% positive. To compare, the company-average is 40.7% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 14 days to get hired, when considering 3 user submitted interviews for this role. To compare, the hiring process at BILL overall takes an average of 22 days.
Common stages of the interview process at BILL as a Data Scientist according to 3 Glassdoor interviews include:
Background check: 20%
Phone interview: 20%
Personality test: 20%
One on one interview: 20%
Skills test: 20%
Here are the most commonly searched roles for interview reports -
1) recruiter call ~15 mins 2) 1 hour tech round, asking 2 sql questions ( not too easy as you need to consider lots of edge cases) and whiteboarding for developing risk strategies
Interview questions [1]
Question 1
1) sql questions 2) whiteboarding for developing risk strategies
I applied online. The process took 2 weeks. I interviewed at BILL (San Jose, CA) in Feb 2025
Interview
I interviewed at BILL.
The overall process took about 2 weeks. Starting with a resume screen, then a recruiter screen, then a Hiring Manager round followed by a Coding round and a Case Study round. Everyone was kind and understanding. The hiring manager tested on resume review and relevant experience and a guestimate. Coding was in SQL and Python. The case study tested quantitative and strategy both.
Interview questions [1]
Question 1
1. Numbers of cars in California. 2. Conditional column in a Pandas DF and time and memory complexity. 3. Window function in SQL. 4. Product efficiency for market entry.
They asked about the previous project experience and dive into some details, and they also asked some questions about data cleaning, and data manipulation. It was not quite difficult. Interviewers are nice.
Interview questions [1]
Question 1
They asked about the previous project experience and dive into some details, and they also asked some questions about data cleaning, and data manipulation