About

Rajat Srivastava is a highly skilled Machine Learning Engineer with over 7 years of relevant experience in the field. He is currently working at Groupon as a Machine Learning Engineer, where he has developed machine learning models using SpaCy and Stanford NLP to cluster tweets into various topics depending on the coherence scores. He has also performed sentiment analysis using transfer learning that will be used to make decisions on insurance products. Rajat has optimized and converted code to Spark to reduce time and improve performance on Databricks Clusters. He has also created a reusable machine learning pipeline using SparkML. Prior to Groupon, Rajat worked as a Machine Learning Student Consultant at Great American Insurance Group, where he developed machine learning models using SpaCy and Stanford NLP to cluster tweets into various topics and performed sentiment analysis using transfer learning for decision-making on insurance products. He also optimized and converted code to Spark to reduce time and improve performance on Databricks Clusters. Rajat has also created a reusable machine learning pipeline using SparkML. Rajat's past experience also includes working as a Senior Software Engineer at Ezetap Mobile Solutions Pvt. Ltd. where he built a data pipeline to move data from MySQL and MongoDB to Redshift for analytics and dashboard use cases. He also designed and developed Ezetap Wallet Payment 2.0 and integrated PayTM, GooglePay, and PhonePe's APIs to the Ezetap system. Rajat has converted monolithic systems to micro-service based architecture separating Wallet APIs from CNP payment APIs. He has also developed a POC for integrating Stripe and TPSL Payment Gateways to Ezetap CNP module. Rajat has performed text extraction and derived valuable insights from application logs to reduce the 50% of cost incurred due to MDR charges on incomplete payments. Rajat holds a Master of Science in Business Analytics and Data Science from the University of Cincinnati Carl H. Lindner College of Business and a Bachelor of Technology in Computer Software Engineering from Dr. A.P.J. Abdul Kalam Technical University. He also completed his high school education from City Montessori School. Rajat's technical expertise includes ML, sentiment analysis, Databricks, NLP, Spark, software engineering, MySQL, MongoDB, and microservices. He is a highly motivated and skilled professional with a passion for machine learning and data science.