Comcast Sr. Data Scientist in New York, New York

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast.

Sr. Data Scientist Data Engineering

Job Summary:

Sr. Data Scientist/Engineer is responsible for leveraging internal and external data to provide insights and information which supports a facts-based decision making process. Provides input into strategy, analysis methods, and tool selection. May work independently or as part of a team on more complex projects. Provides mentoring and guidance to more junior team members.

Role Description:

The team is composed of experts in deep learning, data-structures, algorithms, distributed systems, and system performance and analysis. The systems that the team builds are horizontally scalable, fault-tolerant, and easy to debug. This position is perfect for those scientists/engineers looking to data engineering at scale at scale / distributed systems challenges and unsupervised learning/feature engineering and predictive modeling using massive Comcast datasets.


- Develop data science platform designed to cover the end-to-end ML workflow: manage data, train, evaluate, and deploy models, make predictions, and monitor predictions.

- Develop system that supports traditional ML models, time series forecasting, and deep learning

- Driving execution from start to finish of strategic deep learning projects at all levels

- Researching and implementing algorithms and data-structures for our platform

- Develop load scripts and support development of data pipelines. Proactively problem solve and identify areas of improvement to guide development of industry leading tools.

- Work on ingestion and scoring process from data receipt through storage, deployment and mapping.

- Comfort and experience with the art and science of extruding insight from massive, unstructured data sets

- Strong understanding of database structure, design, of large distributed systems, and statistical concepts

- Creativity to go beyond current tools to deliver best solution to the problem

- Participate in complex interdepartmental data science programs that designs solutions across one or more technologies to ensure proper implementation and usage of algorithms.

- Educate other departments on data science methodologies, concepts and algorithmic advancements.

- Lead development and implementation of scalable big-data driven solutions for accurate and efficient algorithmic inventory. Manage challenges associated with investigating and understanding large datasets, and building models based on Big Data solutions.

- Define enterprise data strategy and data monetization processes through analysis of rich streams of unstructured data to find correlations between events and identify opportunities to optimize defined desired outcomes


- Architecture-you should have opinions on constructing data processing systems and good knowledge of the principles of systems at scale using and big data technologies - Hadoop, Hive, Impala, Spark

- SQL and advanced data processing

- Solid programming skills-Python / Scala / Spark / C / Java

- Computer Science-solid on data-structure, algorithms and complexity

- Knowledge of machine learning, data mining and natural language processing algorithms with special emphasis on advanced algorithms-SVM, random forests, bagging, gradient boosting machines, k-means ,

- Practical experience in predictive modeling including variable selection, data imputation, collinearity diagnostics, factor analysis, variable interaction analysis, etc.

- Exposure to representation learning (including deep learning)

- Ability to communicate complex concepts in easy-to-understand terminology

- Team player with a "can-do" attitude

- Lean-forward bias to find opportunities and drive results

- Ability to work effectively across functions, disciplines, and levels

Preferred Education Level:

- Master's/PhD degree in Computer Science, Engineering, Operations Research or other quantitative field.


- 3 years relevant working experience

- Experience in tech, communications, internet, ecommerce, or media industry preferred

Comcast is an EOE/Veterans/Disabled/LGBT employer