Tencent Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 24 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Tencent.
Tencent
Data Scientist Intern
Intern Easy Positive experience Accept offer 3 rounds
Interview process
Take home Technical screen Recruiter call
Interview formats
Coding Behavioral Technical
The interview process included a take-home assessment followed by two interview rounds. One of these interviews involved a live SQL coding test. The other questions focused on my resume and previous internship experiences, along with some open-ended questions about data comprehension and how data science is applied in particular situations.
Confirmed questions1 question
- When thinking about adjusting character stats in specific games, what factors would you take into account?
Tencent
Data Scientist
Mid Average Positive experience Accept offer 4 rounds
Interview process
Technical screen Technical screen Technical screen Recruiter call
Interview formats
Technical Coding Case Behavioral
The interview process involved a coding interview, followed by two tech interviews, and then an HR interview. The tech interviews focused on basic machine learning concepts, your past project work, and some small case studies. We dove deep into discussions about XGBoost and bipartite graphs.
Confirmed questions1 question
- Could you provide an explanation of XGBoost?
Tencent
Data Scientist
Senior Average Neutral experience No offer 1 round
Interview process
Recruiter call Technical screen
Interview formats
Technical Case
Started with a resume review, then moved to a case study that was open-ended. I finished by asking about the daily tasks of a data scientist at Tencent. It wasn't very technical overall, and I'm not sure if there will be another round.
Confirmed questions1 question
- How would you manage missing data?
Tencent Data Scientist Interview Questions
Quoted word for word from Tencent interview reports.
“What is the difference between SVM and Logistic Regression?”
Read reports →“What is the method for determining variable importance within a random forest?”
Read reports →“Explain the difference between bagging and boosting.”
Read reports →“How would you add a number to a sorted list?”
Read reports →“Can you explain the differences between Xgboost and LightGBM?”
Read report →“Could you provide an explanation of XGBoost?”
Read report →“Can you explain the difference between an MCP tool and a function-call?”
Read report →“Can you explain your understanding of XGBoost?”
Read report →“When thinking about adjusting character stats in specific games, what factors would you take into account?”
Read report →Formats, difficulty and experience
Across all 24 Tencent interview reports.