Jun 2018 – Feb 2020 · 1 yr 8 mos · Gurugram, Haryana, India

• Simulation platform: Built a scalable and extensible simulation platform from scratch which replicates the relay system behavior incorporating core relay algorithms like Vehicle allocation engine, Pilot allocation engine etc and made it close to real operating system. The usecases include testing multiple strategies, generating training data for ML models
• Network automation: Formulated Network equations to calculate the comprehensive value of a demand which considers nearly 15 factors (gross margin, dry run, wait time for return load and on relay points, network balance etc ) and deciding what demands to accept followed by optimal matching with the supply. Took the entire system to production. 10% improvement in system gross margin per hour achieved on simulation engine
• Predictive engine: Developed machine learning based predictive models for various system parameters like wait time for load at a location, wait time for a trip at its relay points, detention of vehicles. These are consumed by the Network Automation engine
• Pilot resource planning: Developed a stochastic gradient descent based algorithm to get optimal pilots to hire at each location considering all system parameters and their variabilities. 15% improvement in vehicle, 8% improvement in pilot utilities achieved on simulation engine
• Pilot allocation: Developed a graph implementation for triggering the pilot movements from an excess location to a shortage location by predicting the demand-supply gap. 33% reduction in wait times of vehicles at relay points achieved on simulation engine
• AI based conversational agent: Developed an interactive AI Based CRM Agent as part of an internal Hackathon using DialogFlow, Twilio
• Network design: Did geospatial analysis of demands and worked on redesigning the network. 25% reduction in extra kms run observed

May 2017 – Jul 2017 · 2 mos · Greater Bengaluru Area