About

Jineet Doshi is a Staff Data Scientist at Intuit and an AI Lead with a strong background in Computer Science. With over 6 years of relevant experience, he has a proven track record of building end-to-end machine learning models that significantly improve business metrics, from reducing fraud to saving millions of dollars. He is interested in Explainable AI and co-chaired a popular workshop on the subject at KDD 2019. Jineet has worked with leading researchers on state-of-the-art deep learning projects at Carnegie Mellon University. He has experience working with big data tools such as Hadoop, Spark, and Hive, and has built effective machine learning models in production environments. He has also worked on a Google-funded project to build the next generation IoT stack and developed mobile apps and IoT solutions that have been used by consumers worldwide. Jineet is a strong leader with a passion for leveraging technology for good. He was one of the youngest Steering Committee members in IEEE history and helped manage a program engaging IEEE members in 36 countries to build solutions for local communities. Currently, Jineet is a Senior Data Scientist at Intuit, where he led the design and development of a credit risk machine learning model estimated to save $4 million a year. He also designed, developed, and shipped to production a machine learning model to gauge risk and determine payment options at checkout, which runs on 10 million customers and saves $2.4 million a year. Jineet co-owned the entire machine learning model life cycle, from data analysis to model monitoring. In the past, Jineet worked as a Data Scientist at Intuit, where he designed, built, and shipped to production a machine learning model to stop Account Takeovers across all Intuit products. He also architected and wrote new features that improved multiple machine learning models in production in the security, risk, and fraud domain. Jineet holds a Master's degree in Information Technology from Carnegie Mellon University and a Bachelor's degree in Computer Science and Electronics from Dhirubhai Ambani Institute of Information and Communication Technology. He also co-chaired the Explainable AI Workshop at KDD conference 2019 and received 32 paper submissions from 11 countries, the highest for an Intuit hosted workshop.