About

Manish Devatha is an experienced Data Science professional with a passion for technology and a drive to learn new skills. As the Vice President of Credit & Obligor Risk Analytics at Citi, Manish is responsible for developing foundational models and improving forecasting by exploring different machine learning methods. He is proficient in SQL, Python, Spark, and R, and spends his days wrangling large financial data sets to create easy-to-understand dashboards that explain the results. Manish's previous experience includes working as an Assistant Vice President of Credit & Obligor Risk Analytics at Citi, where he developed stress-testing models to estimate loss severity for a $1 trillion banking portfolio by applying various statistical techniques. He also analyzed GBs of unstructured financial data to develop structured data for quantitative analysis of Loss Given Default models. Manish improved data validation processes by building analytical tools and algorithms to automatically identify data anomalies, designed live dashboards, built two-step models for LGD, and evaluated the performance of models in production. Additionally, he developed and designed predictive analytics-based solutions to assess critical risk-weighted assets. Before joining Citi, Manish worked as an Application Developer Intern at Raymond James, where he improved the efficiency of projects by automating project management lifecycle using Python, .NET, and UIpath. He also programmed and deployed RPA bots to migrate data from multiple legacy ERP systems to a new centralized system. Manish established and drove implementation of best practices, coding standards, and other improvement initiatives, and worked with Product Owners and Business Analysts to execute project plans for implementation projects. Manish holds a Master's degree in Business Analytics and Information Systems from the University of South Florida and a Bachelor's degree in Electronics and Communications Engineering from R.V. College of Engineering, Bangalore. He has over 5 years of relevant experience and is skilled in Senior Software Engineering, SQL, Spark, Python, Machine Learning, and Data Science.