Lead Data Scientist at Comcast in Philadelphia, Pennsylvania

Posted in Other 13 days ago.

Type: Full Time

Job Description:

Business Unit: Job SummaryResponsible 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. Acts as a key contributor in a complex and crucial environment. May lead teams or projects and shares expertise. Core Responsibilities- Develop and deploy predictive models based on historical data that provide future predictions about customer behavior- Develop data mining, machine learning, statistical and graph-based algorithms designed to analyze massive data sets for business insights and partner with the data engineering team to ensure proper implementation and usage of algorithms- Mentor a small group of less experienced team members on analytical projects or on cross-functional teams. Frequently serves as team lead on multiple projects, mentor and train junior team members.- Review and approve methodologies used for advanced analysis projects (predictive models, clustering/segmentation, etc) by junior team members and others- Mentor complex projects using wide breadth of data sciences and advanced techniques.- Manages the review, revision and maintenance of existing internal procedures to ensure quality and efficiency. - Determine appropriate methods, prove viability of selected method and educate internal teams as to the analytical foundation.- Use analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools, and machine learning techniques and statistics (e. g., predictive models, LTV, propensity models).- Lead large scale projects that utilize online & offline data, structured & unstructured data, set top box data (media/behavioral/attitudinal) to build customer centric models and optimization tools. Skills- Intermediate to Expert level proficiency with statistical probabilistic modeling techniques such as regression, tree-based methods (Random Forest, GBM), neural networks, support vector machines, supervised/unsupervised clustering techniques (k-means, DBSCAN, Expectation Maximization), principal component and factor analysis, etc.- Expert working within enterprise data warehouse environments platforms (Teradata, Netezza, Oracle, etc.) and working within distributed computing platforms such as Hadoop and associated technologies such as SQL, HQL, MapReduce, Spark, Storm, Yarn, Kafka, Sqoop and Hive- Expert in at least one programming language such as Python, R, Scala, Julia, C#, Java, C++- Experience in Natural Language Processing (word categorization, topic modeling, application of machine learning to NLP) a plus - Ability to explain complex statistical problems and solutions to laymen.- Has a good understanding of overall business, including financial acumen, ability to convert complex data into insights and action plans, demonstrated in-depth understanding of predictive modeling life cycle and architects projects through implementation Education and Experience-Master's degree, preferably in quantitative fields such as Economics, Statistics, Mathematics, Decision Science, Operational Research, Computer Science or Engineering-PhD in a quantitative field preferred-Generally requires 7-11 years related experience Employees at all levels are expected to:- Understand our Operating Principles; make them the guidelines for how you do your job- Own the customer experience - think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services- Know your stuff - be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences- Win as a team - make big things happen by working together and being open to new ideas- Be an active part of the Net Promoter System - a way of working that brings more employee and customer feedback into the company - by joining huddles, making call backs and helping us elevate opportunities to do better for our customers- Drive results and growth- Respect and promote inclusion and diversity- Do what's right for each other, our customers, investors and our communitiesComcast is an EOE/Veterans/Disabled/LGBT employerPDN-911734ff-a82b-4160-bc09-5c5419d4c03d