Spring Intern - Data Science and Analytics

Job Description

Responsibilities
Our Data Science and Analytics internships are designed to provide interns with real-world experience working on projects in a typical Data Science or Analytics 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. We have a 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.
Opportunities may include (but are not limited to):

Television & Streaming Data Science: This group focuses primarily on decision science analyses to support and inform strategy and key business decisions and building advanced data products to help enable more data-enhanced decision support. Interns will assist with research & development to inform new methodologies. Interns will also contribute to the development of tools and data pipelines, as well as implement predictive and inferential statistical and/or machine learning models.

NBC Entertainment Data Science: The NBC Entertainment Group develops and schedules quality programming for our broadcast and cable brands, including NBC, USA, SyFy, Bravo, E!, Oxygen, and Universal Kids. The Data Science intern will be exposed to exciting new challenges and opportunities arising from today's swiftly changing media landscape. They will work on projects designed to address strategic business questions around how to create, market, and distribute media content. In the process, they will receive hands-on experience with real-world datasets, use popular Data Science technologies, and apply statistical and machine learning techniques to develop insights and inform on business strategies.
One App Data Science and Analytics: This team provides business analysis and insights on new growth opportunities in digital media with a focus on digital advertising, consumer products, and digital video streaming in broadcasting, cable, film, news and, sports. Interns partner closely with digital strategy, finance & business development team to gather requirements. These requirements are used to build models to analyze ROI on TV content licensing deals and guild / residual / participant cost models for various levels of content exploitation. Interns will also analyze and create predictive models, provide analysis and A/B testing, and build out standardized reporting for stakeholders.

Peacock Data Science: This team is focused on building machine learning and statistical models to understand and predict content value and performance, customer journey and lifetime value, and developing recommendation systems. Interns will explore and transform data (e.g., cleansing, discretization, imputation, selection, generalization) to create high quality features for the modeling process. Interns develop a close partnership with the team to build real-time and automated batch pipelines for productizing data science solutions. Gain experience in using big data, relational and non-relational data sources to access data at the appropriate level of granularity for the needs of specific analytical projects.

Peacock Editorial Business Intelligence: This team leverages user data to help customers enjoy the Peacock app. Interns will collaborate across various teams to analyze content performance and determine key drivers for our users. Interns complete end-to-end business intelligence solutions to help make data driven decisions and drive actionable recommendations. Interns have the opportunity to develop presentations on analysis and insights for business stakeholders.

Peacock Marketing Analytics: Interns will learn the fundamentals of marketing a product in its infancy, from KPI measurement to broad strategic initiatives throughout the marketing funnel. Responsibilities include: (1)devising and developing customer segmentation frameworks to inform differentiated engagement and retention marketing strategies at a 1:1 level, (2) identifying areas of strategic opportunity for the marketing team to drive growth and engagement, and inform said strategies with data-driven insights, and (3) designing and developing automated dashboards to better enable self-serve analytics.

Application Deadline: Spring Internship postings are live for a limited time only, apply today!
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Qualifications/Requirements
Current Bachelor's, 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

Cumulative GPA of 3.0 or above

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

Desired Characteristics

Experience with Machine Learning, statistical modeling, predictive modeling, classification models, and clustering a plus.

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

Applied experience creating time-series forecasts in R and/or Python (i.e. ARIMA, Exponential Smoothing, etc.).

Working knowledge of deep learning models and development frameworks such as TensorFlow or PyTorch

Familiarity with Google Cloud Platform, scikit-learn, Spark, Hive, and/or Hadoop

Familiarity with relational databases and SQL. Hands on experience analyzing and mining large datasets in SQL.

Experience with data visualization techniques, concepts, and tools such as Domo, Tableau, Lookr, or Microstrategy

Ability to communicate effectively to both technical and non-technical audiences
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

Jobcode: Reference SBJ-g4jv21-18-226-222-12-42 in your application.