Glassdoor users rated their interview experience at Medal.tv as 100% positive with a difficulty rating score of 3 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for Data Scientist and rated their interviews as the hardest, whereas interviews for Data Scientist and roles were rated as the easiest.
The hiring process at Medal.tv takes an average of 28 days when considering 1 user submitted interviews across all job titles. Candidates applying for Data Scientist had the quickest hiring process (on average 28 days), whereas Data Scientist roles had the slowest hiring process (on average 28 days).
I applied through other source. The process took 2 weeks. I interviewed at Medal.tv (Chicago, IL) in Apr 2025
Interview
My interview experience went very well. I had the opportunity to speak with three team members, all of whom were incredibly friendly and communicated the role and expectations clearly and professionally.
Interview questions [1]
Question 1
This role involves exposure to potentially graphic or harmful material. How do you maintain emotional resilience?
I applied online. The process took 3 weeks. I interviewed at Medal.tv (New York, NY) in Jul 2025
Interview
Behavioral mostly - had a couple of technical interviews mostly to test swift specific knowledge. Aside from that, chatting with various stakeholders at the company, including designers and other engineers.
Interview questions [1]
Question 1
Explaining actor models in iOS, and when tasks run on or off thread
I applied through other source. The process took 4 weeks. I interviewed at Medal.tv (New York, NY) in Mar 2024
Interview
Several rounds of technical interviews, plus a company fit general interview. The company is big on PC games, so is a good place for a gamer, but be prepared to some questions about your gaming habits, etc.
Interviews are nice, interviewers are knowledgeable and ask reasonable questions.
Interview questions [1]
Question 1
How to deal with overfitting, how to organize an A/B testing strategy to estimate an impact of a new feature on business, how to measure statistical significance of the experiment result.