Comcast Software Engineer Intern

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Job Summary

This job code is to be used for internships and co-ops. It is not to be used for temporary or contract workers.

Job Description

Program Overview

Discover opportunities designed to set your career in motion! The Comcast Cooperative Experience internship Program will help you cultivate meaningful relationships, develop strong interpersonal and business skills, gain exposure to the day-to-day operations of a Fortune 40 media and technology company, and receive mentorship opportunities to expand your professional network.

This program immerses students into the daily operation of a contemporary media and technology company while working side-by-side with Comcast’s top innovators. The student becomes an integral part of the Comcast team working on creative, innovative, and thought-provoking projects within various business units.

Organization & Team Overview

The goal of our team is to increase revenue by making ads personalized and serving ads that have high probability of conversion. The Arbitration Engine team is responsible for promotional content relevancy and revenue optimization for customers of TV platforms like X1 set-top boxes, Flex1, and the new Xumo Stream box. Our team works on display advertising and display promotional content. Our team builds distributed systems for serving millions of users, but also builds ML algorithms for relevancy, revenue optimization and protecting end-user's interests in terms of engagement and overall user experience. Mission: "Personalize promotional content placement throughout the browse experience by optimizing for conversion outcomes while automating operator influence, allowing each operator to meet all their unique business goals most efficiently, without affecting users’ engagement" Vision: “Be the best, most customizable promotional content relevancy engine for operators. Be a key differentiating factor for the entOS platform in the market, enabling entOS to attract and retain syndication partners.”

Role Description:

Are you passionate about building systems that serve millions of users? Are you passionate about using machine learning to solve business problems? By you joining our team, you will get a chance to build systems that see large scale, solve interesting challenges of personalizing content for customers, and achieve user happiness and revenue increase at the same time, having a significant impact to the organization.

The student joining our team will be working on building machine learning based applications, data engineering and building metrics, designing online controlled experiments, and building software applications to serve the ML models. The student will be responsible for working on building metrics and feature engineering for some A/B tests, designing and running the A/B tests, building an ML model or an iteration of an existing model, to be used as the treatment group, and implementing the software service side to run the experiment, and analyzing the results from the online controlled experiment. Skills that the student will gain or get exposure to are: Python, PySpark, Databricks, AWS, FastAPI, DynamoDB, Machine Learning, A/B testing, Data Analysis, Feature Engineering, System design and architecture.

Some example projects:

• Based on the user history and preferences, design a machine learning model and an online controlled experiment to go with it, that predicts whether we should show an ad to this user or not, and how many promotional content items we should include in the response for this user.

• Build revenue-based metrics for TVOD, AVOD and other promotional content, which will be used for ML modelling and analytics purposes. Build all the data pipelines needed to continue updating these metrics on an ongoing basis and monitoring these pipelines.

• Automate existing data pipelines deployment, testing,