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.
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Otras evaluaciones sobre las entrevistas para el cargo de Data Management Professional en Bloomberg
Me postulé a través de un reclutador. Acudí a una entrevista en Bloomberg (New York, NY)
Entrevista
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.
Preguntas de entrevista [1]
Pregunta 1
Find any issues in this dataset (picture of a dataset).