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IT Intern (Commercial Analytics) - P&G Information Technology Internship

Salary undisclosed

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Are you a data-savvy strategic player who yearns to make a lasting impact by solving critical business questions for a global industry leader using data, science and technology? P&G Commercial Analytics team is looking for a curious and confident soul who loves cutting-edge technologies, has a solid foundation on computer science, statistics or mathematics, excellent in communicating, and passionate to lead and make things happen!

Our mission is clear- we deliver technology to help win with consumers. Commercial Analytics are diverse business leaders who apply technological skills to deliver ground-breaking business models and capabilities. Whether your role is to build an innovation strategy for a business, protect our critical information systems and assets, or lead a strategic supplier in our cutting-edge shared services organization, your technical skills will be recognized and rewarded.

What We Offer

Our internship program allows you to gain practical hands-on experience with industry leading analytical tools and technologies from Day 1. You’ll be working with passionate cross-functional teams, all while receiving both formal trainings and day-to-day mentoring from our IT and Analytics professionals. As part of this opportunity, you'll also gain access to our comprehensive Data Science capability-building program, designed to enhance your technical skills and expertise.

What Will You Do:

  • Opportunity to be on the Analytics and Insights team taking on retail and media analytics problems that are general across brands,
  • Tasked on real-life projects and responsibilities from Day 1 – understand business objectives and generate impactful insights by investigating datasets of point-of-sales, geospatial, product & supply, DTC, CRM, TV media, online search, etc from more than 10 countries across the region.
  • End-to-End experience in digital product development spanning the entire lifecycle – Build, validate, test and deploy machine learning or other data science models into our IT platforms.