Plymouth Rock Assurance Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 17 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Plymouth Rock Assurance.
Plymouth Rock Assurance
Data Scientist Intern
Intern Difficult Positive experience No offer 1 round
Interview process
Technical screen
Interview formats
Technical
The interview was mainly about technical stuff, especially different models and when to use them. They asked me to pick models for specific situations and explain my choices. It was a good chat and the manager was nice, making it easy to talk. Overall, it was a good interview that really tested my technical knowledge.
Confirmed questions1 question
- Can you tell me about the decision tree model?
Plymouth Rock Assurance
Data Scientist
Mid Average Negative experience No offer 2 rounds
Interview process
Technical screen Onsite
Interview formats
Technical Coding Behavioral
The interview started with a 1-hour round focusing on ML and stats knowledge. The second round, lasting about 4 hours, covered resume discussion, technique questions, and a live coding exercise. The first interviewer was nice, but the second one was offensive, questioning my math major's relevance and poorly framing questions. He also kept dismissing my suggested models and the coding problem had a typo. Instructions and formulas were given in Excel, requiring translation to Python, which was a bizarre experience with that interviewer.
Confirmed questions1 question
- ML basics, stats, background, resume based questions
Plymouth Rock Assurance
Data Scientist
Entry Average Neutral experience No offer 2 rounds
Interview process
Recruiter call Phone screen Technical screen
Interview formats
Technical Behavioral
We had a first round phone interview where they asked basic questions to check my availability and some stats questions like p-value. Then, a second round video interview focused on tech questions, mainly probability (like the coin slip problem) and ML models (pros, cons, and differences between decision trees, random forests, boosting, PCA, etc.).
Confirmed questions2 questions
- Could you define Type I and Type II errors and explain model power?
- What are Type I and Type II errors and the power of the model?
Plymouth Rock Assurance Data Scientist Interview Questions
Quoted word for word from Plymouth Rock Assurance interview reports.
“What is overfitting?”
Read reports →“What are p-values and alpha values in hypothesis testing?”
Read reports →“Could you define Generalized Linear Models (GLMs)?”
Read reports →“What are Type I and Type II errors and the power of the model?”
Read reports →“What is Principal Component Analysis (PCA)?”
Read report →“Could you define Type I and Type II errors and explain model power?”
Read report →“Can you explain the difference between boosting and bagging algorithms?”
Read report →“How would you perform hypothesis testing if there was no alpha value given?”
Read report →“Do you understand gamma distribution?”
Read report →Formats, difficulty and experience
Across all 17 Plymouth Rock Assurance interview reports.