Me postulé en línea. El proceso tomó 2 días. Acudí a una entrevista en Boston Consulting Group (New York, NY) en mar 2025
Entrevista
The process began with a screening covering Python data manipulation and SQL complex queries. This was followed by a technical deep-dive into machine learning algorithms and statistics. The final round was a case study focused on feature engineering and measuring model business impact.
Preguntas de entrevista [1]
Pregunta 1
They asked how I would handle a highly imbalanced dataset for a classification problem, specifically asking which evaluation metrics I would prioritize over accuracy to ensure the model effectively detects the minority class.
One technical round with basic python/EDA/ML questions, followed by a case round, followed by 3 back to back cases. The cases were testing fundamentals, and how you respond under pressure, as well as your communication and applied data science skills
Preguntas de entrevista [1]
Pregunta 1
1. Predictive maintenance case - if you have more time how will you explain to a client how you'll improve a model
2. Random forest - if you have a noisy dataset (lots of features that don't matter) whats the probability of the 2 features of interest being present in any single tree that randomly selects 50 features out of 100
Me postulé a través de otra fuente. El proceso tomó 3 semanas. Acudí a una entrevista en Boston Consulting Group en feb 2026
Entrevista
Coding assessment, involving basic pandas questions towards data cleaning, preprocessing, structuring, and also questions regardind ML.
It involves the need to understand pandas, scikit and numpy very well.
Totally automated via Code Signal.
Acudí a una entrevista en Boston Consulting Group (New York, NY)
Entrevista
First a online One-way interview, then online python coding round, then is a live coding+technical case with real person, last round will be 3 technical cases with partners. Case can be technically challenging
