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
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.
Job Description
The Supply Chain Data Scientist is a key contributor to the team developing decision‑support technologies for Comcast’s Demand & Supply Planning and Network Optimization functions. The role centers on Operations Research, mathematical optimization, and network design, leveraging tools such as Mixed‑Integer Linear Programming, simulation, and heuristic algorithms. Artificial Intelligence and Machine Learning are used where appropriate to support forecasting, demand sensing, and predictive analytics, complementing the core optimization solutions.
The candidate will partner with a US based Data Science team to drive continuous improvement and support the technical design of Data Science and OR initiatives.
Core Responsibilities:
- Design and optimize Linear Programming, Mixed‑Integer Programming, and Simulation models for Supply Chain network, capacity, and inventory decisions.
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Develop and evaluate advanced optimization and OR techniques to solve complex business problems.
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Perform data wrangling, programming, and statistical analysis to support optimization and ML initiatives.
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Build and validate ML models that enhance forecasting, classification, and decision‑making.
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Create training materials and documentation to help teams apply optimization and analytics tools.
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Monitor Supply Chain KPIs to identify opportunities to refine optimization and statistical models.
Knowledge/Skillset:
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You are an analytical and creative thinker, skilled at exploring non‑traditional Operations Research and optimization approaches to complex problems.
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You are a continuous learner, motivated to deepen your expertise in mathematical modeling, optimization, and OR methodologies.
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You are results‑driven and business‑minded, able to clearly communicate optimization logic and analytical insights to diverse audiences.
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You have hands‑on experience with forecasting models using time‑series and/or machine learning techniques.
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You have strong expertise in optimization modeling, including linear programming, mixed‑integer programming, and simulation for solving business and Supply Chain problems.
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You are highly proficient in Python, SQL, Excel, and PowerPoint, using them to build, test, visualize, and present optimization and analytical models.
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You understand modern data ecosystems, including relational databases, data‑warehouse design, cloud storage, and ETL best practices supporting optimization and ML workflows.
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You have experience with GitHub and cloud compute/ML platforms, such as AWS SageMaker, Microsoft Azure, Google Cloud, Kubeflow, or Databricks.
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You excel in project management and cross‑functional collaboration, ensuring smooth delivery of optimization and analytics initiatives.
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You work effectively within global teams, supporting and mentoring less experienced colleagues while learning from senior optimization and OR experts.
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You take initiative and drive Optimization and ML projects end‑to‑end—from problem formulation, data acquisition, and stakeholder alignment to modeling, solution refinement, productionization, and performance monitoring.
Preferred Requirements:
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5+ years of advanced Supply Chain Data Science experience, ideally within Telecom, CPG, or retail replenishment.
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Master’s degree in operations research, Statistics, Supply Chain, Engineering, Computer Science, or related discipline.
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Strong experience in Supply Chain Network Optimization and Inventory Optimization, including mathematical modeling and scenario evaluation.
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Proficiency with optimization tools such as Gurobi, AMPL, or similar solvers/modeling frameworks.
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Experience with BI/reporting tools such as Tableau, Power BI, or QlikView.
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Proven ability to apply data science and optimization techniques to deliver measurable business impact.
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Exceptional communication and collaboration skills, able to partner effectively with technical and business teams.
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Experience in consumer goods or retail environments leveraging advanced modeling to drive operational outcomes.
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Flexibility to collaborate with US based teams and support critical work aligned to U.S. time zones.
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Knowledge of demand planning, forecasting processes, and related metrics (forecast accuracy, bias, demand attainment) is a plus.
Employees at all levels are expected to:
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Understand our Operating Principles; make them the guidelines for how you do your job.
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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.
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Know your stuff - be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
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Win as a team - make big things happen by working together and being open to new ideas.
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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.
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Drive results and growth.
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Respect and promote inclusion & diversity.
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Do what's right for each other, our customers, investors, and our communities.
Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide 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. Please visit the compensation and benefits summary on our careers site for more details.
Education
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.
Relevant Work Experience
5-7 Years
