Anudeep Elavarthy
About Anudeep Elavarthy
Anudeep Elavarthy is a Product Manager with a background in data science and engineering. He has developed various tools and applications that optimize prediction generation and support pricing decisions.
Work at Impact Analytics
Anudeep Elavarthy has held multiple roles at Impact Analytics, starting as a Senior Data Scientist from 2018 to 2019, then advancing to Lead Data Scientist from 2019 to 2022. Currently, he serves as a Product Manager since 2022. During his tenure, he developed a promotion and pricing management application that aids in centralized pricing decisions and includes features for analyzing historical promotions. He also designed a forecast management tool that allows users to simulate, compare, override, and save forecasts, integrating it with MLOps pipelines. Additionally, he created a data platform that integrates various technologies for data sourcing, transformation, storage, validation, and analysis, ensuring data governance and security.
Education and Expertise
Anudeep Elavarthy earned a Bachelor's Degree in Production Engineering from the National Institute of Technology Calicut, where he studied from 2011 to 2015. His educational background has provided him with a solid foundation in engineering principles, which he applies in his current role as a Product Manager. His expertise includes data science, product management, and the development of analytical tools that enhance decision-making processes in business environments.
Background
Prior to his current role, Anudeep worked at Mu Sigma Inc. as a Trainee Decision Scientist from 2016 to 2018 in Bengaluru, India. This early experience in the analytics field contributed to his understanding of data-driven decision-making and set the stage for his subsequent positions at Impact Analytics. His career trajectory reflects a consistent focus on leveraging data science to improve business processes and outcomes.
Achievements
Anudeep Elavarthy has made significant contributions in the field of data science and product management. He created a model that predicts function auto-scaling based on request volume, optimizing prediction generation time for SKUs. His work on various applications and tools at Impact Analytics demonstrates his ability to develop solutions that enhance operational efficiency and support strategic decision-making.