Data Science

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

Data Free 9700+ 5 Star Reviews

Talent Network Open

Get Career Ready

Complete work that simulates life on the job. 6-7 hours and self-paced.

Stand out in your application to BCG. Show us you're a motivated candidate.

Talent Network Open

Get Career Ready

Complete work that simulates life on the job. 6-7 hours and self-paced.

Stand out in your application to BCG. Show us you're a motivated candidate.

Why complete our 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-paced6-7 hoursNo gradesNo assessmentsadvanced

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 is the program for you!

In this job simulation, you will gain enviable insight into what it’s like to solve meaningful challenges with our diverse and forward-thinking team at BCG X. The program 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.

BCG X is transforming 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 and 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.

Talent Network Open

Talent NetworkOpen all year

Skills you will learn and practice:

Business Understanding

Hypothesis Framing

Communication

Programming

Exploratory Data Analysis

Data Visualization

Creativity

Mathematical Modelling

Model Evaluation

Synthesis

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.

Introduction from BCG

Explore Our Job Sims

Tasks in this program

Task One: Business Understanding & Hypothesis Framing

30-60 mins

Advanced

Understanding the business context and problem statement.

What you'll learn

Meet your client PowerCo - a major gas and electricity utility who is concerned about losing customers
How to interpret the business context
How to break down the problem before you start your data analysis

What you'll do

Determine the client data needed for analysis
Outline the techniques you'll use to investigate your client's problem
Write an email to your Associate Director summarizing your approach

Reviews

Over 9700

5 Star Reviews

"it was a great experience working on this project. it was a well versed program with maximum understanding and if we get wrong or are unable to submit a file a clearer ans sheet is given which is great for the beginners to understand."-- Student from Bharati Vidyapeeth Deemed University

"I appreciated the hands-on approach to learning about data analysis and predictive modeling. The structured framework and real-world scenarios provided valuable insights into the challenges of customer churn analysis. The integration of coding with business strategy made the experience both educational and practical, helping me understand how to ap..."-- Student from KLE Technological University

"This was really interesting project to work in and i would like to work for BCG in future if i get opportunity."-- Student from University of Pavia

"I liked the links added to tasks to help learn what was needed to carry out the task. I also liked the problems and the overall learning experience especially as it gives experience of hands on practical knowledge. I learnt a lot from the model answers especially on feature engineering and model design."-- Student from Federal University of Technology, Minna

"It gives me aperfect guidance alongwith all the basic concepts of skills which are going to be used in this project"-- Forager

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