Data Scientist

Comcast•Philadelphia, PA

About The Position

Comcast brings together the best in media and technology, driving innovation to create world-class entertainment and online experiences. As a Fortune 50 leader, Comcast sets the pace in innovative businesses, offering career opportunities across various locations and disciplines. The company is at the forefront of change, moving at an amazing pace thanks to its people who bring cutting-edge products and services to millions of customers daily. The Data Scientist is responsible for solving complex business problems by extracting knowledge and insights from large data sets, particularly unstructured text. This involves using Large Language Models (LLMs) and other AI techniques to extract insights at scale from rich textual data sources. The role enables exploration of unstructured data using techniques like RAG, Knowledge Graphs, and advanced statistical analysis, and augments textual data with additional metadata to generate actionable insights and solutions. The Data Scientist will build pipelines for efficient data processing to enable fast and flexible business insights and explore emerging AI-based techniques, especially agentic workflows, to improve customer experience, products, and go-to-market capabilities. The position requires aligning the technical roadmap to business strategies and ensuring insights are actionable. The team comprises experts in artificial intelligence, deep learning, data structures, algorithms, distributed systems, and system performance and analysis, building systems used across various Company data science-based services and deployments. The role operates with moderate guidance in its area of knowledge.

Requirements

Experience solving complex business problems by extracting knowledge and insights from large data sets, especially unstructured text.
Proficiency in using Large Language Models (LLMs) and other AI techniques to extract insights at scale from textual data sources.
Experience enabling exploration of unstructured data with techniques like RAG, Knowledge Graphs, and advanced statistical analysis.
Ability to augment textual data with additional metadata to generate actionable insights and solutions.
Skill in building pipelines for efficient processing of data to enable fast and flexible business insights.
Ability to explore emerging AI-based techniques, especially agentic workflows, that improve CX, products, and go-to-market capabilities.
Ability to align technical roadmap to business strategies and ensure insights are actionable.
Expertise in artificial intelligence, deep learning, data-structures, algorithms, distributed systems, and system performance and analysis.
Ability to work with moderate guidance in own area of knowledge.
Ability to interact with CX, Strategy, Product, and other business-facing teams.
Ability to generate actionable insights from data quickly.
Ability to build AI-driven processes that are repeatable, flexible, and scalable.
Skill in synthesizing prompts and context by joining multiple data sources for LLM analysis; tracking accuracy and reliability of results.
Effective communication of insights to drive improvement in the business.
Ability to engage with executive levels as appropriate.
Skill in enabling non-technical users to explore unstructured data by building apps, agents, and other tools.
Proficiency in developing and coding software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
Ability to contribute technical ideas and share techniques learned through project work or other experiences.
Knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
Analytical rigor and statistical methods to analyze large amounts of data.
Experience 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).
Experience creating data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets.
Ability to build 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.
Ability to work nights and weekends, variable schedule(s) as necessary.
Master's Degree (or some combination of coursework and experience, or extensive related professional experience).
2-5 Years Relevant Work Experience.

Responsibilities

Interacts with CX, Strategy, Product, and other business-facing teams to identify questions and issues for data analysis and experiments.
Generates actionable insights from data quickly.
Builds AI-driven processes that make these insights repeatable, flexible, and scalable.
Synthesizes prompts and context by joining multiple data sources for LLM analysis; tracks accuracy and reliability of results.
Communicates insights effectively; uses data to drive improvement in the business.
Engages with executive levels as appropriate.
Enables non-technical users to explore unstructured data by building apps, agents, and other tools.
Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
Contributes technical ideas; shares techniques learned through project work or other experiences.
Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
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).
Creates data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets.
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.
Consistently exercises 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.
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.
Support a culture of inclusion in how you work and lead.
Do what's right for each other, our customers, investors and our communities.

Benefits

An array of options, expert guidance and always-on tools that are personalized to meet the needs of your reality—to help support you physically, financially and emotionally through the big milestones and in your everyday life.

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