Analyst 4, Enterprise Data Analytics - VIRTUAL

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.

Job Summary

This is a VIRTUAL role.

This role sits within Comcast’s West Division finance organization. Our diverse team leads a variety of data-driven work for the entire West Division of Comcast. We take extremely large, complex datasets and turn them into a variety of types of tools, predictions, and recommendations for one of the largest businesses in the country. We use our technical expertise to give our colleagues in other disciplines the answers they need to do their jobs in better, more data-driven ways.

Job Description

Core Responsibilities

• • Participate in defining business intelligence requirements for projects and data requests. 

  • Formulate and test hypotheses, weigh alternatives and determine appropriate recommendations for actionable insights. 

  • Participate in multiple enterprise-wide projects by providing data analysis to project leaders. 

  • Provide training to and act as technical resource for team members. 

  • Produce an often-complex collection of reports, graphs, summaries and presentations that convey analytic results and align with business needs. 

  • Design new methods and best practices for analysis and presentation of comparative data. 

  • Vet recommendations to determine viable options and provides business case to management. 

  • Serve as a team leader within a work group or on cross-functional teams; accept team lead stretch assignments. Lead discussions and presentations of results, recommendations and business insights to broader senior leadership team. 

  • Perform in-depth research on root cause of data anomalies that are uncovered through normal course of analysis. 

  • Collaborate with both the analytic organization and its technology partners to define and publish complex data products. 

  • Write complex SQL to query large data platforms such as Teradata and SQL server to obtain data necessary for analysis. Combine data as needed from disparate data sources to complete analysis. 

  • Create technical documentation (internal). 

  • Consistently exercise independent judgment and discretion in matters of significance. 

   

  While we expect these to be the role's typical duties, team members may sometimes have to tackle other responsibilities as necessary, and occasionally overtime or non-standard work hours might be needed. 

  Traits We Value For this Role Include: 

  • An advanced degree in a quantitative field (e.g., economics, engineering, the sciences, statistics, etc.), or equivalent practical experience, that demonstrates you can tackle new problems from end-to-end in a quantitative way with modern tools. 

  • Fluency in SQL or a similar database language. We use Teradata, Trino, and SQL Server extensively, and other databases as needed. 

  • Fluency in Python (and its major data packages) or a similar general purpose scripting language. Our team mostly uses Python for data-analysis-related scripting and a bit of C# for some tools. 

  • Experience translating complex analysis results into easy-to-understand business recommendations comprehensible to a non-technical audience, using great visualizations in the process. 

  • Experience designing processes to extract, transform, and load complicated data from disparate data sources. 

  • Comfort selecting the right statistical tools given a data analysis problem, and knowledge of how to quantify your confidence in measurements obtained with those tools. 

  • Comfort working in, and perhaps leading, teams of varying skill levels and disciplines. 

  • Eagerness to teach yourself a difficult new skill when the best tool for the job is a totally new one. 

  • Understanding of basic machine learning best-practices. Our team is not an ML engineering team, but we sometimes need to make forecasts or predictions. 

  • Experience documenting and teaching your complex knowledge or analysis in a way that benefits your whole team. 

  • Exp