How to prepare for BCG's Data Scientist technical case interview?

To prepare for BCG’s Data Scientist technical case interview, focus on blending business problem-solving with technical reasoning, it’s not just coding, but how you apply data science to drive impact.

Here’s how to prepare effectively:

Understand the format:

• You'll likely be given a business scenario (e.g., customer churn, pricing, operations)
• Your task: define the problem, propose a data-driven solution, and explain your methodology (e.g., modeling choices, feature selection, data limitations)
• Some interviews may include SQL, Python, or model interpretation exercises, depending on the office and role

What to focus on:

1. Structure your thinking like a consultant
   • Start with: “What’s the business objective?”
   • Break down: What data would you need? How would you model it? What insights would matter most to the business?
2. Brush up on key topics
   • Supervised learning (regression, classification)
   • Unsupervised learning (clustering, PCA)
   • Model evaluation (cross-validation, metrics)
   • Communication of results to non-technical stakeholders
3. Practice “technical storytelling”
   • Can you explain your model choices in plain business terms?
   • Can you prioritize trade-offs (accuracy vs. interpretability, data volume vs. latency)?

Practice Resources:

• Kaggle case studies (focus on business problems, not leaderboard optimization)
• StrataScratch or LeetCode (SQL + ML)
• BCG X candidate prep (if available via recruiter)

Hi,

For the the Data Scientist interview (which used to be Gamma, now called X), you will be tested on both a combination of business thinking (i.e. normal case interview), but more importantly the interviewer will weave in questions around how you would approach the problem from a data science POV. (e.g. what analytical approach would you use? how would you think about setting up the data? etc).

You can easily find someone to help you prep for the 'business' POV but you would need someone who has a background in Data Science to really help on the true technical aspect.