La procedura ha richiesto 4 settimane. Ho sostenuto un colloquio presso Chartboost nel mese di gen 2023
Colloquio
Very smooth and fast.
Four steps:
- Initial interview with recruiter
- Technical exercise (SQL, python)
- Talking to engineering VP
- Talking to manager to evaluate capacity to solve a DS problem from ML perspective
- Talking to another random person for cultural fit
- Talking to another CTO
- Final offer
Domande di colloquio [1]
Domanda 1
Usual DS interview questions such as:
- How would you solve X problem
- Which data sources could you use for feature engineering
- ... etc.
They were very fast with all communication. For me there were 4 rounds of interviews: 1. general talk with the recruiter 2. Data Science talk with the Director of Engineering about previous projects you have done 3. Live coding session in Hackerrank. There were a total of 4 questions and a minimum of finishing 2. 2 SQL questions which consistent of creating a query with several conditionals and returning a result. 2 Python questions, of which I only did one. The python question was about a tuple and you had to create a loop with multiple conditions. 4. talk with a project manager (I did not get to this round). This seemed to be role for data scientist that know very well how to code (by heart), which for me was a bit of a pity because Data Science is a lot more than only coding.
Domande di colloquio [1]
Domanda 1
Previous projects & Hackerrank questions in SQL and Python
The recruiter was very gentle and the manager was awesome. the manager spends a good time explaining the process and the projects they are working on and they allow for questions
Domande di colloquio [1]
Domanda 1
SQL : how many users visit the website daily? he gave two tables
SQL: the revenue / by daily visitors
- A case study of click rate : what are the metrics used to examine the performance of a machine learning model implemented to improve the click rate?
- How can we choose the sample for testing the model in live ( the model above)
