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NBCUniversal


New York, NY

www.nbcuniversal.com
Watch Company Video

Jobs

Data Science Internships – Summer 2021, Remote

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Posted on: January 13, 2021 Apply Now
Paid Internship Expires February 1, 2021

About Us

Our Summer 2021 Internship program will be fully remote, and after successfully hosting virtual interns over the last year, we’re ready to make Summer the best experience yet! Our internships are true learning and growth opportunities that help students set themselves up for an exciting future career in media. NBCUniversal is committed to developing early career talent, and in this unprecedented time we remain even more focused on helping our interns realize their potential and their dreams.

NBCU interns are a diverse and curious community of innovators and trail blazers. They bring their passion for media, entertainment, and technology along with their desire to learn each day. They contribute to our vast and diverse portfolio of businesses in hands-on ways that matter. We provide a program full of countless opportunities for professional development, leadership exposure, connection, networking, and fun.

Responsibilities:

Our Data Science program is designed to provide interns with real-world experience working on projects on a typical Data Science environment, using state of the art tools and technologies, while gaining broad exposure to the media industry. Interns will acquire specific responsibilities, goals, and timelines aligned with the teams they are embedded in. Join the world-class team of smart, hungry and fearless professionals who are working at the cutting edge of technology and science at the epicenter of content, technology and culture.

Daily responsibilities and projects may include (but are not limited to):

Assisting with research & development to inform new methodologies

Implementing predictive and inferential statistical and/or machine learning models

Contributing to the development of tools and data pipelines

Building advanced recommender engines, active learning platforms, and personalized solutions for marketing and advertisement

Application Deadline: Summer Internship postings are live for a limited time only, apply today!

Qualifications/Requirements:

Current Master’s or PhD student at an Accredited Institution in Data Science, Computer Science, Operations Research, Statistics, Mathematics, Economics, or other relevant quantitative fields. Must be able to provide documentation to confirm your degree progress

Working knowledge of at least two of the following programming languages: R, Python, Julia, Java, Scala or similar

Prior experience with Machine Learning and/or statistical modeling

Advanced working knowledge of statistics and its applications for inferential data analysis

Familiarity with Spark, Hive and/or Hadoop

Familiarity with relational databases and SQL

Experience with data visualization techniques and concepts

Cumulative GPA of 3.0 or above

Must be 18 years of age or older

Must be authorized to work in the United States without visa sponsorship by NBCUniversal

Desired Characteristics:

Strong interest in the media industry

Commitment to building an inclusive work environment

Strong interpersonal skills; must be able to work effectively as part of a project team and foster team cooperation

Excellent verbal and written communication

Previous internship experience and on-campus involvement

Notices:

NBCUniversal’s policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. NBCUniversal will consider for employment qualified applicants with criminal histories in a manner consistent with relevant legal requirements, including the City of Los Angeles Fair Chance Initiative For Hiring Ordinance, where applicable.

Apply Now

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