Ankita Bhatia
About Ankita Bhatia
Ankita Bhatia is a Data Analyst with extensive experience in data analytics and software engineering. She has held various positions at GE and Infosys, where she established a data-analytics team and led projects in digital industrial applications.
Current Role at ThoughtWorks
Ankita Bhatia has been working as a Data Analyst at ThoughtWorks since 2019. In this role, she focuses on leveraging data analytics to support various projects. Her expertise includes building applications using R-Shiny, which aids biologists in visualizing the underlying concepts of learning algorithms for models. This position highlights her commitment to applying data-driven insights in practical scenarios.
Previous Experience at GE
Ankita Bhatia held multiple roles at GE, contributing significantly to various projects. She served as a Senior Design and Analytics Engineer for 8 months in 2019, where she established the Data-Analytics team in the Life Sciences division of GE Healthcare in Bangalore. Prior to that, she worked as a System Specialist from 2016 to 2019 and as a Senior System Engineer from 2013 to 2016. During her tenure, she coordinated cross-disciplinary teams and led software application development using agile methodologies.
Career at Infosys
Before her time at GE, Ankita Bhatia worked at Infosys as a Senior Software Engineer from 2010 to 2013. In this role, she was involved in software development projects, contributing her technical skills and knowledge to deliver effective solutions. This experience laid the foundation for her subsequent roles in data analytics and engineering.
Educational Background
Ankita Bhatia completed her Bachelor of Technology (B.Tech.) in Information Technology at Raj Kumar Goel Institute of Technology from 2006 to 2010. This educational background provided her with a solid foundation in technology and engineering principles, which she has applied throughout her career in various analytical and engineering roles.
Machine Learning Development
Ankita Bhatia has developed industrial use machine learning models that currently have an estimated accuracy of 70% and are in the Beta phase. This work showcases her ability to apply machine learning techniques to real-world problems, further enhancing her expertise in data analytics and software development.