BCG | Internship Opportunity in Data Science & Analytics, Apply Now!
BCG is inviting an Internship in Data Science & Analytics. Interested ones can apply.
In this virtual experience program, you will gain enviable insight into what it’s like to solve meaningful challenges with our diverse and forward-thinking team at BCG GAMMA. The program will show you what kind of problems are solved at BCG GAMMA and will attempt to simulate the challenges you will be facing – new terminology, ambiguity about the client goal, and challenging data analysis. All those aspects form an integral part of our day-to-day work.
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, test 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.
How will you benefit?
- This Virtual Experience is free for everyone
- This program is self-paced. It takes 5-6 hours in total to complete this program.
- Get practical skills and experience from BC
- BCG actively recruits passionate, open-minded, and accomplished learners at colleges and universities around the world.
What will you learn?
- Business Understanding & Hypothesis Framing: Understanding the business context and problem statement.
Exploratory Data Analysis: Understanding the business through data
Feature Engineering & Modelling: Uncovering signals within the data, predicting churn probability, and evaluating model performance
Findings & Recommendations: Presenting your results and giving recommended actions to the client
This program is self-paced. It takes 5-6 hours in total to complete this program.