About

Hema Penumatsa is a highly skilled Machine Learning Engineer with over 7 years of experience in the field. She is currently working as a Senior Machine Learning Engineer at Iterable, where she is responsible for developing statistical analysis, feature engineering, and ML and DL algorithms. She is also an expert in model tuning, optimization, and AWS deployments in NLP and forecasting related products. Prior to joining Iterable, Hema worked as a Senior Machine Learning Engineer at Clarify Health Solutions and Change Healthcare. At Clarify Health Solutions, she developed feature embeddings and predictive models for insurance coverage predictions. At Change Healthcare, she implemented scalable deduplication and blocking predicates pipelines for clustering in AWS eco system using Airflow, Gitlab CI/CD, EMR, Spark, Glue, and Athena. She also worked on NLP and rule-based models for claims denial predictions using OCR features of medical documents. Hema holds a Master's degree in Industrial and Systems Engineering (Specializing in Data Analytics) from San Jose State University and a Bachelor's degree in Mechanical Engineering from Amrita University. She is proficient in several technologies, including ML, Data Science, AWS, NLP, Deep Learning, Spark, Apache Airflow, Amazon Athena, and CI/CD. Overall, Hema is a highly motivated and skilled Machine Learning Engineer with a proven track record of delivering successful projects. She is passionate about leveraging her expertise to create innovative solutions that drive business growth and success.