Ahsin Shabbir
The client was a USA restaurant with over 2800 restaurant locations. They were looking to improve their order forecasting system and have a contractor develop a custom solution that meets current and future business needs. The solution worked with 2 billion daily transaction records and achieved 94% accuracy saving the company $18million annually.
I worked closely with the client's product owner to create the project requirements.
I lead a team of 5 developers to create a custom forecasting solution for the restaurant chain. The forecasting pipelines ingest "raw" transaction records, aggregate them into 15 minute increments, and then use that as input to train a model. The model is trained to forecast orders up to 6 weeks out and at a 15 minute granularity. The forecasts are then loaded into json format into DynamoDB and used by the restaurant operators through a web application that gives them suggested order notifications. When the forecast anticipates high demand in the upcoming 6-week window, the operators can place the order in advance to ensure there is enough inventory on-hand. The solution is entirely self-sufficient and continues to operate without any additional development effort.
.. and many more skills that were needed to complete this challenging (but fun) project!
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