Shashank Jain

Orchestrated the integration and strategic analysis of a proactive churn prevention model using Athena Kafka Workflow for real-time late delivery tracking, resulting in a 5% increase in GB and trips in the Taiwan market. Developed regression-based models for accurate GB and FTE targeting for AM in OneMartech Budget Allocation. Built a Flask-based dashboard for interactive result analysis. Conducted research and developed various model orchestrations leveraging Michelangelo for procuring MLOps pipeline.

Led scoring architecture development at Cars24 using Django, refining loan policies and risk mechanisms, improving scoring system by 20% and scaling using Kubernetes. Automated end-to-end model deployment with Cloud Functions, integrating lead prioritization from insights through ML model deployment. Implemented kserve architecture for organizing ML models, improving real-time prediction by 40%, and enabling canary deployment for traffic management. Designed feature store with Feast for online feature storage, facilitating training, retraining, and insights gathering for real-time predictions.

Demonstrated proficiency in API Development using Flask Rest API framework, facilitating communication between Python applications and Swagger UI to interact with MongoDB. Deployed entire applications using DevOps principles, utilizing Microservices containers like Docker and Kubernetes for efficient scaling. Automated deployment processes using Ansible scripts, resulting in a 50% performance increase compared to manual deployment methods. Gained expertise as a full stack developer, employing Java with Spring Framework and Angular to develop a customized single-page web application.