Société Générale Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 31 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Société Générale.
Société Générale
Data Scientist
Entry Average Neutral experience No offer 3 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Technical Coding Behavioral
It was a nice and smooth interview process. They asked basic DSA and ML questions, along with Probability and Statistics, Data Preprocessing, Cleaning, Data extraction, data visualisation, ML techniques, Project based questions, and resume based questions. Overall it was a smooth virtual interview experience.
Confirmed questions1 question
- Can you explain what Multicollinearity is and how you'd identify it?
Société Générale
Data Scientist
Mid Difficult Positive experience No offer 4 rounds
Interview process
Recruiter call Technical screen Phone screen Onsite
Interview formats
Behavioral Technical Coding
The first contact was made on LinkedIn with another data scientist from the IGAD department. My CV was sent to their manager and interviews were scheduled a few days later. I went through 4 interviews: the first was with a recruiting HR, preceded by personality, logic, and English tests. During this interview, the results were reviewed, and the HR asked me to talk about myself (why this profession, this choice of study, etc.). Then came an interview with the manager, who presented the position, the department, and the types of tasks, followed by technical questions on ML/DL. Next was an interview with the business HR, where my background was discussed. The last interview was technical: data preprocessing with Pandas on Jupyter, using groupby, etc. The interviews were quite long (from 12:30 PM to 6:30 PM without a break).
Confirmed questions3 questions
- Can you explain the difference between RNN and LSTM?
- How can you prevent an autoencoder from learning the identity function?
- What is a key feature of an autoencoder?
Société Générale
Data Scientist Intern
Intern Average Positive experience Accept offer 2 rounds
Interview process
Recruiter call Onsite Offer
Interview formats
Behavioral Technical
I applied online for a Data Scientist Intern role, and after 2 weeks, I was contacted back and had an interview in Fontenay. The interview lasted about 1 hour and 15 minutes, with one person from the team and one from HR. The interview went very well, and the atmosphere was relaxed and friendly. The interview covered my education, my professional experience, and the field of Data Science. In addition to questions about my work style, what I like about the job, etc...
Confirmed questions3 questions
- Could you explain supervised and unsupervised learning?
- Can you describe a Machine Learning algorithm?
- How would you define Big Data?
Société Générale Data Scientist Interview Questions
Quoted word for word from Société Générale interview reports.
“What is a key feature of an autoencoder?”
Read reports →“How can you prevent an autoencoder from learning the identity function?”
Read reports →“What is the underlying mathematical hypothesis for unsupervised classification?”
Read reports →“What are the uses and applications of KL divergence?”
Read reports →“What is another unsupervised algorithm besides k-means and hierarchical clustering?”
Read report →“Can you explain the difference between RNN and LSTM?”
Read report →“Can you explain Batchnorm and its role in forward and backward passes?”
Read report →“What are the different types of machine learning models and how are they evaluated?”
Read report →“What are some regularization methods and how do they work?”
Read report →Formats, difficulty and experience
Across all 31 Société Générale interview reports.