The hiring process at Scalpel.ai takes an average of 25 days when considering 1 user submitted interviews across all job titles. Candidates applying for Data Scientist had the quickest hiring process (on average 25 days), whereas Data Scientist roles had the slowest hiring process (on average 25 days).
I applied through a recruiter. The process took 1 week. I interviewed at Scalpel.ai (London, England) in Jan 2025
Interview
I would avod this company as it shows bad practices. After a technical interview discussion, you will have to provide a full technical report with code that is directly correlated to their core technical problems. The technical "problem" is open enough for them to get as much as possible from your ideas and code. You won't get any feedback on what was expected or what was the correct solution.
Interview questions [1]
Question 1
Technical assignement related to their core technical problems
I applied online. The process took 1+ week. I interviewed at Scalpel.ai in Dec 2022
Interview
Founder invited me to an initial conversation - spent an hour asking each other questions about company/vision and my experience. Got ghosted, despite the founder saying they'd reach out again to me next day, no response on LinkedIn message - very unprofessional.
Interview questions [1]
Question 1
Generic experience in health care and product management questions, and how I'd fit in to make the company reach the next level.
I applied online. The process took 3 weeks. I interviewed at Scalpel.ai (London, England) in Nov 2019
Interview
Brief call then a coding challenge. Coding challenge was very tedious taking approx 2-3 full days. After completing the challenge, no response for two weeks. Only after my second follow up I got a response saying the position has been filled already.
Interview questions [1]
Question 1
Objective: Create a blood loss model from the other data points.
Tasks:
Write a Python script to do the following including explanation.
- Data preprocessing
- Account for the fact that some data points are missing
- Determine a baseline result using unsupervised learning
- Finally, use a neural network to create a predictive model