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Calico Life Sciences Data Scientist Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 7 interview experiences · FREE TO READ

3.4 Rounds average
Average Typical difficulty
28.6% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Calico Life Sciences.

Showing 3 of 7
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Calico Life Sciences

Data Scientist

Analytics · more than a year ago

Mid Difficult Positive experience Accept offer 4 rounds
Interview process
Recruiter call Phone screen Technical screen Onsite
Interview formats
Technical Coding Behavioral

Had some phone interviews, then an all-day on-site. They asked technical stuff and about my past work and what I'd do in the future. They really care about specific skills they need right now, and if you have 'em. It's not just about being technical, gotta show you're excited too. For me, one interview was like a coding challenge on a laptop, had to write working code for a problem in about 30 mins. Pretty standard coding question.

Confirmed questions1 question
  • Write a quick function to find a number N and its k preceding and succeeding neighbors in a sorted list. Handle cases where N isn't present (find nearest), duplicates, and boundary limits for k. Avoid errors.
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Calico Life Sciences

Data Scientist

Analytics

Senior Difficult Negative experience No offer 6 rounds
Interview process
Recruiter call Take home Phone screen Onsite Background check Offer
Interview formats
Behavioral Technical Coding Presentation

The interview process kicked off with a recruiter call where they went over the company, the job details, and policies like the mandatory 3-day on-site requirement (Tuesdays and Wednesdays non-negotiable) and pay. After that, I got a technical take-home assignment with data and questions. Then, I had a video chat with the hiring manager. The next step was a full day on-site, which included a presentation and interviews with various team members and the hiring manager. About a week later, I followed up with the recruiter, who told me they were checking my references. Finally, there was a verbal offer discussion and negotiation via video call with the same recruiter. A week after that, I found out they decided not to extend a formal offer. The whole thing took 3 months.

Confirmed questions3 questions
  • Can you tell me about your strengths and weaknesses?
  • Describe how you would vectorize R code.
  • How would you tackle these particular statistical challenges?
Calico Life Sciences logo
Calico Life Sciences

Data Scientist

Analytics

Mid Average Neutral experience No offer 3 rounds
Interview process
Recruiter call Phone screen Take home
Interview formats
Behavioral Technical

It started with an HR phone call to get a feel for my general knowledge about the company. Then, I had a call with the Hiring Manager where we talked about my general scientific interests. After that, there was a take-home technical project. Honestly, the take-home wasn't too hard and didn't really connect to my research background, which felt like a bit of a wasted effort given my PhD. The team didn't seem that interesting to me either, and it felt like a role with limited scientific independence. Ultimately, it wasn't a good fit for me.

Confirmed questions1 question
  • Can you describe an instance where you took the lead on a project?

Calico Life Sciences Data Scientist Interview Questions

Quoted word for word from Calico Life Sciences interview reports.

Write a quick function to find a number N and its k preceding and succeeding neighbors in a sorted list. Handle cases where N isn't present (find nearest), duplicates, and boundary limits for k. Avoid errors.

Read reports

Can you explain stochastic modeling, Markov chains, and Hidden Markov models?

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How would you tackle these particular statistical challenges?

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Can you describe an instance where you took the lead on a project?

Read report

Formats, difficulty and experience

Across all 7 Calico Life Sciences interview reports.

Interview formats

Behavioral 37.5%
Technical 37.5%
Coding 12.5%
Presentation 12.5%

Interview difficulty

Easy 14.3%
Average 57.1%
Difficult 28.6%

Candidate experience

Negative 42.9%
Neutral 28.6%
Positive 28.6%