Sr. Analyst, Enterprise Analytics

Nitel•Philadelphia, PA

About The Position

Our analysts transform data into meaningful insights that drive strategic decision making. They analyze trends, interpret data, and discover opportunities. Working cross-functionally, they craft narratives from the numbers - directly contributing to our success. Their work influences key business decisions and shape the direction of Comcast. Responsible for extracting knowledge and insights from high volume, high dimensional data in order to investigate complex business problems through a range of data preparation, modeling, analysis and/or visualization techniques, which may include the use of advanced statistical analysis, algorithms, predictive modeling, experimentation and pattern recognition to create solutions that enable enhanced business performance. Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. The team is composed of experts in artificial intelligence, deep learning, data-structures, algorithms, distributed systems, and system performance and analysis. The systems that the team builds get used across the multitude of Company data science-based services and deployments. Works independently with minimal-to-no supervision while also demonstrating the ability to lead projects and initiatives autonomously.

Requirements

Machine Learning (ML)
Data Analysis
Data Science
Master's Degree
While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.
5-7 Years Relevant Work Experience

Responsibilities

Interacts with product and service teams to identify questions and issues for data analysis and experiments.
Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
Uses 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, lifetime value, propensity models).
Develops and executes statistical and mathematical solutions to business problems to support larger initiatives under the direction of senior team members.
Creates data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets.
Works with large, noisy, and complex datasets to produce analysis of historical patterns in customer behaviors and product performance from complex real-world behavioral data.
Develops and deploys predictive models based on historical data that provide future predictions about customer behavior.
Constructs forecasts, recommendations and strategic/tactical plans based on applying data science techniques to business data.
Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
Creates deliverables and presentations that report methodology and results of analysis.
Builds customer centric models and optimization tools to support large scale projects that utilize online and offline data, structured and unstructured data, set top box data and media/behavioral/attitudinal data.
Consistent exercise of independent judgment and discretion in matters of significance.
Regular, consistent and punctual attendance.
Must be able to work nights and weekends, variable schedule(s) as necessary.
Other duties and responsibilities as assigned.