Summer Remote Intern - Data Engineering

Job Description

Responsibilities
Our Data Engineering internships are designed to provide interns with real-world data engineering experience, using state-of-the-art tools and technologies. Working as part of our data engineering teams, interns will help to design and develop custom decision sciences product for the media industry. Interns will acquire specific responsibilities, goals, and timelines aligned with the teams in which they are embedded. Our teams collaborate across our businesses to design and implement engineering solutions that drive data-enhanced strategic decisions.
Opportunities may include (but are not limited to):

Peacock Data Engineering: This team is responsible for architecting solutions that clean, format, and pipe data downstream to Peacock's data analytics teams as well as Peacock's various business partners. Interns have the opportunity to gain exposure to and experience with the most cutting-edge data streaming technology in the industry. Interns will develop solutions combining data blending, profiling, mining, statistical analysis, and machine learning, to better define and curate models, test hypothesis, and deliver key insights. Interns will continually work on improving the codebase and have active participation in all aspects of the team, including agile ceremonies.

Television & Streaming Data Engineering: This group works closely with partners across NBCUniversal's businesses to drive advanced analytics throughout the company. The data engineering team processes structured and unstructured data into a form suitable for analysis and reporting, to drive state-of-the-art analytics and machine learning applications. They partner closely with data scientists to understand processes and support feature engineering. Interns will assist in operationalizing data science models and products in a cluster-computing environment. Interns will also build data pipeline frameworks to automate high-volume / real-time data delivery.

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

#LI-Remote

Qualifications/Requirements
• Current Bachelor's, Master's or PhD student at an Accredited Institution in Computer Science, Data Engineering, ML Engineering, or other relevant fields. Must be able to provide documentation to confirm your degree progress
• Working knowledge of at least two of the following programming languages: Python, R, PySpark, Angular, JavaScript, Java
• Must be authorized to work in the United States without visa sponsorship by NBCUniversal

Additional Job Requirements

Must submit an attestation disclosing your COVID-19 vaccination status and, if partially or fully vaccinated, submitting your vaccination record no later than 7 days following commencement of employment.

Must be fully vaccinated against COVID-19 at the commencement of employment or must undergo regular COVID-19 testing if Company determines your job position requires accessing an NBCUniversal worksite.

Must be willing to adhere to all Company COVID-19 workplace safety policies and protocols.

Desired Characteristics
• Cumulative GPA of 3.0 or above
• Students with class standing of junior or above preferred.
• Working knowledge of Distributed Computing environment
• Experience with Machine Learning and/or statistical modelling
• Experience working in cloud computing environments, such as GCP and AWS, designing solution architecture
• Experience with Docker or other container systems
• Experience with Git or other version control solutions
• Familiarity with relational databases and SQL
• Familiarity with data visualization techniques (knowledge of BI tools a plus: Tableau, Domo, etc.)
• 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

Jobcode: Reference SBJ-dyw69q-3-131-13-194-42 in your application.