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Data Science Engineer at Comcast (Philadelphia, PA)

Comcast's Technology & Product organization works at the intersection of media and technology. Our innovative teams are continually developing and delivering products that transform the customer experience. From creating apps like TVGo to new features such as the Talking Guide on the X1 platform, we work every day to make a positive impact through innovation in the pursuit of building amazing products that are enjoyable, easy to use and accessible across all platforms. The team also develops and supports our evolving network architecture, including next-generation consumer systems and technologies, infrastructure and engineering, network integration and management tools, and technical standards.

As a Data Science Engineer in Comcastdx, you will research, model, develop, support data pipelines and deliver insights for key strategic initiatives. You will develop or utilize complex programmatic and quantitative methods to find patterns and relationships in data sets; lead statistical modeling, or other data-driven problem-solving analysis to address novel or abstract business operation questions; and incorporate insights and findings into a range of products.

Assist in design and development of collection and enrichment components focused on quality, timeliness, scale and reliability. Work on real-time data stores and a massive historical data store using best-of-breed and industry leading technology.

Responsibilities:

-Develop and support data pipelines

-Analyze massive amounts of data both in real-time and batch processing utilizing Spark, Kafka, and AWS technologies such as Kinesis, S3, ElastiSearch, and Lambda

-Create detailed write-ups of processes used, logic applied, and methodologies used for creation, validation, analysis, and visualizations. Write ups shall occur initially, within a week of when process is created, and updated in writing when changes occur.

-Prototype ideas for new ML/AI tools, products and services

-Centralize data collection and synthesis, including survey data, enabling strategic and predictive analytics to guide business decisions

-Provide expert and professional data analysis to implement effective and innovative solutions meshing disparate data types to discover insights and trends.

-Employ rigorous continuous delivery practices managed under an agile software development approach

-Support DevOps practices to deploy and operate our systems

-Automate and streamline our operations and processes

-Troubleshoot and resolve issues in our development, test and production environments

Here are some of the specific technologies and concepts we use:

-Spark Core and Spark Streaming

-Machine learning techniques and algorithms

-Java, Scala, Python, R

-Artificial Intelligence

-AWS services including EMR, S3, Lambda, ElasticSearch

-Predictive Analytics

-Tableau, Kibana

-Git, Maven, Jenkins

-Linux

-Kafka

-Hadoop (HDFS, YARN)

Skills & Requirements:

-5-8 years of Java experience, Scala and Python experience a plus

-3+ years of experience as an analyst, data scientist, or related quantitative role.

-3+ years of relevant quantitative and qualitative research and analytics experience. Solid knowledge of statistical techniques.

-Bachelors in Statistics, Math, Engineering, Computer Science, Statistics or related discipline. Master's Degree preferred.

-Experience in software development of large-scale distributed systems including proven track record of delivering backend systems that participate in a complex ecosystem

-Experience with more advanced modeling techniques (eg ML.)

-Distinctive problem solving and analysis skills and impeccable business judgement.

-Experience working with imperfect data sets that, at times, will require improvements to process, definition and collection

-Experience with real-time data pipelines and components including Kafka, Spark Streaming

-Proficient in Unix/Linux environments

-Test-driven development/test automation, continuous integration, and deployment automation

-Excellent communicator, able to analyze and clearly articulate complex issues and technologies understandably and engagingly

-Team player is a must

-Great design and problem-solving skills

-Adaptable, proactive and willing to take ownership

-Attention to detail and high level of commitment

-Thrives in a fast-paced agile environment

About Comcastdx:

Comcastdxis a result driven big data engineering team responsible for delivery of multi-tenant data infrastructure and platforms necessary to support our data-driven culture and organization.dxhas an overarching objective to gather, organize, and make sense of Comcast data with intention to reveal business and operational insight, discover actionable intelligence, enable experimentation, empower users, and delight our stakeholders. Members of thedxteam define and leverage industry best practices, work on large-scale data problems, design and develop resilient and highly robust distributed data organizing and processing systems and pipelines as well as research, engineer, and apply data science and machine intelligence disciplines.

Comcast is an EOE/Veterans/Disabled/LGBT employer