J'ai postulé via un recruteur. Le processus a pris 4 mois. J'ai passé un entretien chez Bloomberg
Entretien
- 1st round - HR round questions about data structures and their use cases
-2nd round - Python programming around data structures, problems involving data basic data structures(lists, dictionaries etc) , Basic ML and stats(measures of central tendency etc),error calculations for ml
-3rd round- Pandas questions, Was given a Bloomberg dataset.
-Final round - Senior Manager, Motivation based questions mainly.
Questions d'entretien [1]
Question 1
1st round - Interviewed last year and had a leetcode style questions, this time around however the questions were Bloomberg and role specific eg from a list remove invalid words(think of it as a data cleaning but with basic data structures) .
2nd round - Best advice is practice using kaggle on as many datasets as possible, stratascratch is okay but found kaggle more useful.
J'ai passé un entretien chez Bloomberg (Hong Kong)
Entretien
Consists of 3 parts. The first is a leetcode-easy python coding problem. The next is a real-world solution based on statistical knowledge. The last is a taxonomy problem that requires you to find out flaws in the original one.
J'ai postulé via un recruteur. J'ai passé un entretien chez Bloomberg (New York, NY)
Entretien
I was contacted by a recruiter for the role. After an initial HR screening, there were four rounds of interviews. The first round was with the hiring manager/team lead and focused on my previous experience and general questions related to the role. The second round was a technical interview with two team members and included a live Python coding exercise. The third round was a take-home Excel assessment with basic questions related to financial statements. The final round was on-site with two team leads and included a mix of behavioral questions and discussion about past experience.
For the Python round, focus on solving LeetCode easy-level questions and reviewing basic Data Modeling, ML and Stats.
Overall, it was a positive experience and HR was quick with updates throughout the process.
The first round was behavioral, followed by a technical interview focused on data modeling concepts and data quality considerations rather than coding. The second technical round involved exploratory data analysis using Python and pandas.
Questions d'entretien [1]
Question 1
Find any issues in this dataset (picture of a dataset).