Sr. ML Engineer

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

Bring a combination of mathematical rigor and innovative algorithm design to create recipes that extract relevant insights from billions of rows of data to meaningfully improve Comcast user experience. 

Do you like big challenges and working within a highly-motivated team environment? As a Data Scientist, you will research, develop, support and apply new techniques using real-time distributed computing architectures. You will employ your skills to deliver insights into customer and network behavior to drive business decisions that will shape the future of Comcast and be part of a team that thrives on big challenges, results, quality, and agility. 

Who does the Data Scientist work with? 

The Data Engineering and Science team as part of our Next Generation Access Network is a diverse collection of professionals who work with a variety of organizational roles ranging from software engineering teams whose software integrates with analytics services, network architects and engineers, to service delivery engineers who provide support for our product, testers, operational stakeholders with all manner of information needs, and executives who rely on data for data based decision making.  

What are some interesting problems you’ll be working on? 

Develop models capable of processing millions of events per second and multi-billions of events per day, providing both a real time and historical view into the operation of our products and services. Work on high performance real time data stores and a massive historical data sets using best-of-breed and industry leading technology. Work closely with various engineering teams to solve key optimization, insight and access network data challenges. 

Where can you make an impact? 

The Comcast Next Generation Access Network Data Engineering and Science team is acquiring, studying, simulating, and modeling to enable data as a key driver and core functional component toward better understanding, predicting, and dynamically optimizing the access network to improve overall user experience. Success in this role is best enabled by a broad mix of skills and interests ranging from traditional distributed systems software engineering prowess to the multidisciplinary field of data science.  

Job Description

Core Responsibilities

• Building a strong intuitive understanding of the problem domain (Next Generation Access Networks). Identify testable hypotheses to explain interesting phenomena in this domain. 

• Selecting and transforming features, building and optimizing classifiers using machine learning techniques 

• Integrating data from multiple sources including third party sources. 

• Data mining using state-of-the-art methods 

• Enhancing data collection procedures to include information that is relevant for building analytic systems 

• Frequent meeting/communication with stakeholders to interpret their needs, plan/organize, and discuss progress and results 

• Developing actionable quantitative models in the areas of effectiveness, ROI, pricing and optimization. 

• Doing ad-hoc analysis and presenting results in a clear manner 

• Creating automated anomaly detection systems and constant t