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Data Science

Location: United States

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

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 dataExploratory data analysis & data cleaning: understanding the customers’ data and its statistical properties as well as preparing a dataset for further analysisFeature engineering: using business context and expertise to create new data that may provide useful signals in the prediction of outcomesModeling 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.

This program is self-paced. It takes approximately 6-7 hours to complete.

Skills Learned:

  • Business Understanding & Hypothesis Framing
    Understanding the business context and problem statement.

    • Business Understanding
    • Hypothesis Framing
    • Communication
  • Exploratory Data Analysis
    Understanding the business through data

    • Programming
    • Exploratory Data Analysis
    • Data Visualization
  • Feature Engineering & Modelling
    Uncovering signals within the data, predicting churn probability and evaluating model performance

    • Creativity
    • Mathematical Modelling
    • Model Evaluation
  • Findings & Recommendations
    Presenting your results and giving recommended actions to the client

    • Synthesis
    • Client Communication
    • Model Interpretation
  • Finish Line

Experience Information

Sponsor
BCG
Learn More
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Contact & Location

Phone
612.330.1148
Email
careers@augsburg.edu
Website
http://augsburg.edu/strommen
Address

Christensen Center, Suite 100

Minneapolis, MN 55454

Career Service Hours

M Monday 9:00 am- 4:00 pm
T Tuesday 9:00 am- 4:00 pm
W Wednesday 9:00 am- 4:00 pm
TH Thursday 9:00 am- 4:00 pm
F Friday 9:00 am- 4:00 pm

Meet the Team

Morgan Knutzen Meet Morgan
Gina Musto Meet Gina
Ma Xiong-Nguyen Meet Ma
Marcus Carrigan Meet Marcus
Learn More
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