Built ML model pipeline for Shipping Prices

In my role as an SDEat Amazon, I partnered with the Data Scientists to address a redundancy issue in delivery price calculations. We noticed certain ship offers required repeated computations, leading to identical delivery prices.

The repeated calculations for the same delivery prices resulted in unnecessary latency for our services. This slowed down the overall process and led to inefficiency in our operations.

Using my skills in Java and AWS, I worked closely with the AI team to build a pipeline. This pipeline trained our AI model to predict delivery prices for frequently seen ShipOptions, enabling quick delivery price vend.

With the new AI model pipeline, we managed to significantly reduce service latency as we no longer had to call our dependent services and perform complex calculations. This not only sped up our operations but also enhanced the efficiency of our delivery pricing system.