Data Science Intern

Key Skills

Python Programming, R Programming, Statistical modeling

Job Description

Keurig Experiences Data Science Intern

As a data-science intern at Keurig Dr. Pepper you will be a part of our beverage revolution. You will learn, enhance and apply your curiosity and analytic skillset to help us improve customer understanding and provide a competitive advantage for our Keurig business teams.

Each intern will have real responsibilities and will be provided opportunities to grow professionally. 

Come learn what it takes to succeed at an industry-leading company and help contribute to our ongoing success.

• You will engage and partner on innovative data science projects to gain experience in a fast paced, cross functional team environment
• You will receive mentor support for your professional development
• You will present a final presentation to your team, peers, and senior leaders to highlight your project work and impact on the business
• You will network and learn about other functions at Keurig through a Lunch & Learn series

What you will do:

• Apply data exploration and analysis techniques to examine clickstream, point of sale (POS), and IOT data from multiple disparate sources.
• Apply statistical and predictive modeling concepts, clustering and classification techniques, and recommendation algorithms to help optimize customer targeting, reduce churn, and increase customer life-time-value.
• Translate and break apart day-to-day business challenges into manageable segments for data science application.
• Navigate many multi-functional stakeholders, and communicate technical results effectively to non-technical audiences.
• Implement strategic analyses with the know-how to balance getting the details right, while still moving at the speed of business.

Requirements

What you must have:

• Must be a Bachelor or Masters student currently enrolled in a full-time academic program with extensive analytical coursework (Mathematics, Statistics, Computer Science)
• Knowledge of statistical and predictive modeling concepts.
• Experience with one or more statistical analysis and scripting tools, including R, Python.
• Critical thinking and problem solving skills.
• Excellent organizational skills and attention to detail with demonstrated ability to manage multiple projects, prioritize requests, and meet deadlines.
• Strong communication skills including excellent listening, written and verbal abilities.