I applied online. The process took 2 weeks. I interviewed at Boston Consulting Group in Mar 2024
Interview
I applied online, then HR called me after that I received a code signal test link based on probability and ml MCQ and python coding, with medium difficulty. Post that i had two rounds of interviews based on our profile, projects worked on, questions based on ml, python data manipulation questions and casestudy. I didn't get any call post that, but there are totally three rounds of interview
Interview questions [1]
Question 1
1) case study problem
2) R^2, Auc, precision,Recall
3) python based on pandas
4) Parameter tuning
I interviewed at Boston Consulting Group (Bengaluru)
Interview
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.
Interview questions [1]
Question 1
Simple ML questions:
- Bagging
- Boosting
- Logistic Regression
- Random Forest
- Decision Trees
I applied online. I interviewed at Boston Consulting Group (Bogotá, Bogota) in Mar 2026
Interview
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).
I applied online. I interviewed at Boston Consulting Group (Casablanca, Greater Casablanca) in Feb 2026
Interview
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.
Interview questions [1]
Question 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.