Summer 2021 Data Science Intern

New York, New York, United States

Applications have closed

Take-Two Interactive Software, Inc.

Take-Two Interactive Software is a leading game publisher, creating games through its labels, Rockstar Games, 2K, Private Division, and Social Point.

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Who We Are:

Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for consumers around the globe. For more than 25 years, our development teams have created some of the most critically acclaimed and commercially successful entertainment experiences, captivating and engaging audiences around the world. We are incredibly proud of our ability to deliver consistently the highest-quality titles, as well as our colleagues who help to create our unique culture and work environment that is inclusive, diverse, and dynamic.

While our offices are casual and inviting, we are deeply committed to our core tenets of creativity, innovation and efficiency, and individual and team development opportunities. Our industry and business are continually evolving and fast-paced, providing numerous opportunities to learn and hone your skills. We work hard, but we also like to have fun, and believe that we provide a great place to come to work each day to pursue your passions. 

The Challenge

In this internship, you will experience the full cycle of model development from conception to production.  This role is structured around designing and delivering a demand forecasting model for Take-Two’s video game products.  You will learn about corporate data practices, the interactive entertainment business, and what it takes to deliver a model into production.  You will work with a data scientist who will serve as your mentor and supervisor to guide you through this project.  The model you build will ultimately be used to help inform strategy decisions for the Commercial team as well as fiscal guidance and planning decisions for Take-Two and its labels.

What You’ll Take On

  • Learn about Take-Two’s data systems
  • Gain understanding of current body of forecasting methodologies
  • Work with your mentor to propose a new forecasting methodology
  • Develop a plan to execute your methodology and build the model in Python
  • Work with your mentor to interface with the data engineering team to bring your model to production

What You Bring

  • Python, SQL, probability/statistics
  • BA/BS in a quantitative discipline
  • Current or recently graduated Masters/PhD student

What We Offer You:

  • Great Company Culture. Ranked as one of the most creative and innovative places to work, creativity, innovation, efficiency, diversity and philanthropy are among the core tenets of our organization and are integral drivers of our continued success.
  • Growth: As a global entertainment company, we pride ourselves on creating environments where employees are encouraged to be themselves, inquisitive, collaborative and to grow within and around the company.
  • Work Hard, Play Hard. Our employees bond, blow-off steam, and flex some creative muscles – through corporate boot camp classes, company parties, game release events, monthly socials, and team challenges.

 

Take-Two Interactive Software, Inc. (“T2”) is proud to be an equal opportunity employer, which means we are committed to creating and celebrating diverse thoughts, cultures, and backgrounds throughout our organization.  Employment at T2 is based on substantive ability, objective qualifications, and work ethic – not an individual’s race, creed, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin or ancestry, alienage or citizenship status, physical or mental disability, pregnancy, age, genetic information, veteran status, marital status, status as a victim of domestic violence or sex offenses, reproductive health decision, or any other characteristics protected by applicable law.

Tags: Engineering PhD Python SQL Statistics

Perks/benefits: Career development Team events

Region: North America
Country: United States
Job stats:  96  29  0

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