Data Science

Use data to advise your client, PowerCo, on how to retain their customers with the team at BCG X

Complete work that simulates life on the job. 8-9 hours and self-paced.
Stand out in your application to BCG. Show us you're a motivated candidate.

Why complete this Job Simulation

A risk-free way to experience work on the job with us at BCG. Practice your skills with example tasks and build your confidence to ace your applications.

Self-paced

8-9 hours

No grades

No assessments

Advanced

Are you a curious problem solver with a passion for working with data? Do you have some experience with programming and statistics? Are you interested in how Artificial Intelligence is implemented in the real world? Then this simulation is for you!

At BCG, our purpose is to unlock the potential of those who advance the world. We do this by partnering with leading companies to help them solve their most complex challenges. In this job simulation, you will gain enviable insight into what it’s like to solve these meaningful challenges with our diverse and forward-thinking team at BCG X. The simulation will show you what kind of problems are solved at BCG X and will attempt to simulate the challenges you will be facing – new terminology, ambiguity about the client goal, challenging data analysis. All those aspects form an integral part of our day-to-day work.

At BCG X, we are technologists, scientists, programmers, engineers, and human-centered designers who build to address the world's most important challenges and opportunities. We transform the businesses of today through data science and analytics initiatives. Our goal is to help companies generate competitive advantage through these insights. This program is designed to give you a feel of what it is like to work at BCG X as we help our clients using data science.

Data science is a large market of opportunity and expertise within BCG. When tackling a business problem there are typically 5 high-level steps that we follow:

Business understanding & problem framing: understanding the context of the customer and the problem they’re trying to solve with data
Exploratory data analysis & data cleaning: understanding the customers' data and its statistical properties as well as preparing a dataset for further analysis
Feature engineering: using business context and expertise to create new data that may provide useful signals in the prediction of outcomes
Modeling and evaluation: Using your engineered dataset to model an outcome and generate predictions. Then, testing these predictions against the ground truth to see whether they are reliable.
Insights & Recommendations: turning the insights of this analysis into business decisions and recommendations.

Each of the tasks in this program aligns to a stage in the data science process and follows a real-world example to bring it to life.

We recognize that these tasks are challenging and that there are undoubtedly phrases and terminology you may not have heard before – don’t worry! We have tried to make this experience as true to life as possible and therefore our ask is that you attempt to seek out independent sources of information and do your own research, as required, to help guide you through the tasks.

Disclaimer: Participation in this job simulation is not an employment relationship with BCG. It is our policy that you do not list your completion of this program as work or internship experience on your CV, LinkedIn, or any other social media or professional platform. For guidance on how to accurately represent your experience, review the Forage CV referencing policy.

How it works

Complete tasks guided by pre-recorded videos and example answers from our team at BCG. No live sessions, all self-paced.
Earn a certificate and add it to your resume and LinkedIn as an extra curricular activity.
Stand out in applications. Confidently answer interview questions and explain why you’re a good fit for our team.

Skills you will learn and practice:

Business Understanding

Client Communication

Communication

Creativity

Data Visualization

Exploratory Data Analysis

Hypothesis Development

Information Synthesis

Mathematical Modeling

Model Analysis

Model Assessment

Programming

Tasks

Task One: Background Information

30-60 minsIntroductory

Reviews

4.6

The progression mirrored a real project arc. Framing the problem → EDA → feature engineering → modeling → executive summary is genuinely how a data science case unfolds at a firm like BCG. Each task built directly on the last (the churn column from Task 2 fed into Task 3's features, which fed into Task 4's model), so nothing felt like a disconnected exercise.

Student

I liked the simulation because it gave me a practical opportunity to apply data science concepts to a real-world business problem. I especially enjoyed exploring the data, creating meaningful features, building a churn prediction model, and translating the results into actionable business recommendations. It also helped me understand how data-driven insights can support better business decisions.

Student

I enjoyed working on a real-world customer churn prediction project. The simulation helped me improve my skills in exploratory data analysis, feature engineering, machine learning, and presenting business recommendations. It provided a practical understanding of how data science is applied in consulting.

Student