Supply Chain Data Scientist 3

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.

Responsible for extracting insights from large, complex datasets to solve challenging business problems using advanced data science techniques. This includes data preparation, exploratory analysis, predictive modeling, forecasting, and visualization to drive better decision-making and business outcomes. The role focuses on developing scalable data science solutions that leverage statistical modeling, machine learning, and time-series forecasting to improve demand planning, supply chain performance, and operational efficiency. The team builds and deploys data-driven solutions across a wide range of applications, utilizing modern data platforms, cloud technologies, and machine learning frameworks. This position operates with a high level of autonomy while contributing to cross-functional initiatives and leading data science projects end-to-end.

The Supply Chain Data Scientist plays a key role in developing forecasting and predictive analytics solutions to support Comcast’s Demand & Supply Planning functions. This role emphasizes time-series forecasting, demand sensing, and machine learning-driven insights to improve planning accuracy and responsiveness. You will partner with a U.S.-based Data Science team to enhance forecasting capabilities, develop scalable models, and drive continuous improvement in supply chain analytics.

Develop and deploy time-series forecasting models to improve demand planning accuracy across products and regions. Build and evaluate machine learning models for demand sensing, anomaly detection, and predictive analytics. Perform data wrangling, feature engineering, and exploratory analysis on large-scale supply chain datasets. Design and implement end-to-end data science pipelines for forecasting and predictive use cases. Analyze and monitor forecast performance metrics (i.e. accuracy, bias, attainment) and continuously improve model performance. Partner with business stakeholders to translate data insights into actionable recommendations. Create documentation, dashboards, and visualizations to communicate insights and model outputs. Collaborate with cross-functional teams to productionize and scale data science solutions. Knowledge/Skillset: Strong foundation in data science and forecasting, including time-series models (ARIMA, Prophet, XGBoost and other ML-based forecasting approaches). Experience applying machine learning techniques to real-world business problems, particularly in demand forecasting or predictive analytics. Proficiency in Python, SQL, Excel (PowerPivot), and PowerPoint, using them to build, test, visualize, and present optimization and analytical models. Understand modern data ecosystems, including relational databases, data‑warehouse design, cloud storage, and ETL best practices supporting optimization and ML workflows. Experience with GitHub and cloud compute/ML platforms, such as AWS SageMaker, Microsoft Azure, Google Cloud, Kubeflow, or Databricks. Excel in project management and cross‑functional collaboration, ensuring smooth delivery of optimization and analytics initiatives. You take initiative and drive Optimization and ML projects end‑to‑end: from problem formulation, data acquisition, and stakeholder alignment to modeling, solution