Better model workflows for retail pricing.
Maintaining and improving an AI-driven system used to optimize pricing during seasonal sales.
Role: Senior Data Scientist. Scope: Existing pricing system and forecasting experiments. Selected technologies: Python, Google Cloud, Vertex AI and BigQuery.
This work comes from Eslam’s previous consulting experience.
The context
The system supported seasonal sale pricing. Its operation involved model training, evaluation and selection, with demand forecasting as an area for further experimentation.
Eslam’s contribution
Eslam maintained and enhanced the system and improved its training, evaluation and model selection processes. He designed demand forecasting experiments and provided technical recommendations across modeling and production operations.
The work delivered
The contribution combined ongoing system support with improvements to the model workflow. It connected experiments with the practical requirements of an existing operational system.
Where this experience is relevant
An established machine learning system that needs continued support, a stronger evaluation process or a clearer connection between model development and production operation.
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