Jeel Sheth Email & Phone Number

Bengaluru, Karnataka, India

Bengaluru, Karnataka, India

- Collaborated with a team of 4 in developing an order management system for the recently launched E-commerce platform Pincode, in line with the ONDC contract. Integrated with Finite State Machine, Databuilder, and Grafana libraries to ensure fomaintainability and extendability.- Designed a logistics management service by integrating with multiple third-party providers, including Shadowfax, resulting in a 40% increase in successful deliveries and on-time deliveries without breaking TAT, and a 11% reduction in customer tickets.- Designed a content automation service to generate sellers' marketing content, potentially increasing seller engagement and reducing content creation time. Conducted a POC enabling the design team to submit templates that can be converted into formats like images based on seller inputs. Also explored and implemented sharding for high scalibitly. - Developed a dashboard for customer support agents to quickly and efficiently view order information, track order status, and effectively address customer inquiries and issues

Mumbai, Maharashtra, India

• Designed and implemented a configurable anomaly detection utility by decoupling the existing prediction and monitoring systems making detections faster by 83%.• Improved user experience by adding an aggregated view of the current job statuses to an existing monitoring dashboard.

Mumbai, Maharashtra, India

• Revamped the notification rule engine allowing for different user configurations and making the system reliable by sending timely notifications consisting of probable causes, impact information in case of faults.• Reduced the failure rates of Python engine in case of large input data size by reading and writing the input data from a file rather than sharing it over socket-based communication protocol.• Adding functionality to support different input datatypes like files, training models in our Python engine.

Ahmedabad Area, India

--> The objective of the project is to generate small videos using the given rich contextual data.--> Surveyed through various research papers to get a glimpse of different existing methods which include concepts like text encoding, image encoder, Generative Adversarial Networks, Conditional Variational Autoencoder, etc. --> Implemented an end-to-end model taking reference from one of the studied paper.