Ketki Savle
About Ketki Savle
Ketki Savle is a Senior Machine Learning Scientist currently employed at Carelon and previously at Anthem, Inc. She specializes in developing scalable natural language processing solutions for healthcare applications and has a strong background in information technology and machine learning.
Work at Carelon
Ketki Savle has been employed as a Senior Machine Learning Scientist at Carelon since 2022. In this role, she focuses on developing advanced natural language processing (NLP) solutions tailored for healthcare applications. Her work aims to improve the machine understanding of natural language, which is crucial for enhancing healthcare services. Prior to her position at Carelon, she worked at Anthem, Inc. as an AI Senior Machine Learning Scientist, where she contributed to similar projects.
Education and Expertise
Ketki Savle holds a Master's degree in Information Technology from the University of North Carolina at Charlotte, which she completed from 2017 to 2019. She also earned a Post Graduate Diploma in Business Administration with a focus on Operations Management and Supervision from Symbiosis Institute of Management Studies between 2013 and 2015. Additionally, she obtained a Bachelor of Engineering (B.E.) in Information Technology from Thadomal Shahani Engineering College from 2007 to 2010. Her educational background supports her expertise in machine learning, deep learning, and cloud computing.
Professional Background
Before her current roles, Ketki Savle served as an Adjunct Faculty at Government Polytechnic College for eight months in 2011-2012. She also worked as a Graduate Teaching Assistant at the University of North Carolina at Charlotte from 2017 to 2019. These positions provided her with valuable teaching experience and a strong foundation in academic and practical applications of technology.
Achievements in Machine Learning
Ketki Savle specializes in Information Extraction and Information Retrieval from clinical text, focusing on healthcare applications. She is part of a team dedicated to creating scalable NLP solutions that enhance the understanding of natural language within the healthcare sector. Her technical skills include proficiency in software development using PyTorch and Python, which are essential for building state-of-the-art machine learning models.