Candidatei-me online. O processo levou 3 semanas. Fui entrevistado pela Boston Consulting Group (Casablanca, ) em out. de 2025
Entrevista
Le processus a commencé par un test technique sur CodeSignal avec des exercices de programmation et d'analyse de données assez complexes. Ensuite, j'ai eu un entretien avec les RH pour discuter de mon parcours et de mes motivations. Le niveau de difficulté du test CodeSignal était élevé, avec des questions avancées en SQL, Python et résolution de problèmes algorithmiques. Durée totale du processus : environ 2-3 semaines.
Perguntas de entrevista [1]
Pergunta 1
Test CodeSignal avec 3 notebooks : analyser et nettoyer des datasets avec Pandas/NumPy (gestion des valeurs manquantes, groupby, merge), puis implémenter et évaluer un modèle d'arbre de décision avec des métriques de performance
Fiz uma entrevista na empresa Boston Consulting Group (Bengaluru).
Entrevista
I attended the initial online assessment, where there were MCQ questions on statistics, probability, machine learning, and three coding problems on Python. We had to do data analysis, EDA, feature engineering, and fitting the model and creating a prediction file.
Perguntas de entrevista [1]
Pergunta 1
Simple ML questions:
- Bagging
- Boosting
- Logistic Regression
- Random Forest
- Decision Trees
Candidatei-me online. Fui entrevistado pela Boston Consulting Group (Bogotá, Bogota) em mar. de 2026
Entrevista
The interviewer was very friendly, he explained everything I think he did not leave anything out in terms of salary and benefits, he also explained what would be needed for the technical assessment. In my case, Python (Numpy, Pandas, Scikit-learn).
Candidatei-me online. Fui entrevistado pela Boston Consulting Group (Casablanca, ) em fev. de 2026
Entrevista
I applied online through the BCG careers page. After about a week, I received an email inviting me to complete a proctored CodeSignal Data Science Framework assessment. The assessment was 90 minutes long and contained 5 questions covering data cleaning, data preprocessing, training a ML classifier, aggregating data from multiple files using joins and groupbys, and a probability calculation. The time pressure was significant. I did not advance past this stage.
Perguntas de entrevista [1]
Pergunta 1
Given a dataset of drivers with multiple CSV files, clean the data, preprocess features using scikit-learn (imputation, encoding, scaling), and train a classifier to predict a driver's class.
