Nishant Yadav

E-margin product: Boosted revenue through targeted strategies: Leveraged e-margin for intraday traders and adjusted leverage policies, resulting in a 13-15% exposure increase. Orchestrated a successful contest for growth. Enhanced MF-SIP performance: Evaluated SIP lifecycle, and pinpointed dealer misconduct related to incentives/KRA. Achieved execution rise from ~45% to ~55% in recent 2 months, curbing persistency decline from -25% to -16%.

Recommendation Engine for Shopping Website: Designed and deployed an end-to-end recommendation system for a Shopping website, leveraging Spark ALS, FPM, Python Implicit, and Apriori algorithms. Utilized MLFlow on Databricks for model tracking and served optimized recommendations, enhancing user engagement. Predictive Analysis for Pig Farms: Integrated and analyzed 7 datasets for a Pig Farms project, crafting regression/classification models to predict distinct types of pig mortality. Resulting insights empowered effective mitigation strategies, improving overall farm outcomes. AWS Data Lake Design: Built a data lake using services like Glue, Athena, Lambda, and Kinesis Streaming service. Integrated AWS services with Databricks by creating IAM roles on AWS & used it in Databricks workspace as an instance profile.