Gurbaksh Sharma
About Gurbaksh Sharma
Gurbaksh Sharma is a Senior Data Scientist at Treasure Data, where he has worked since 2021. He has a strong background in data science, with expertise in customer analytics and marketing strategies.
Work at Treasure Data
Gurbaksh Sharma has been serving as a Senior Data Scientist at Treasure Data since 2021. He operates from Bengaluru, Karnataka, India, in a remote capacity. In this role, he focuses on leveraging data science techniques to enhance business intelligence and customer insights. His contributions include the development of advanced analytical frameworks that support marketing strategies and customer engagement initiatives.
Previous Experience in Data Science
Prior to his current position, Gurbaksh Sharma worked as a Data Scientist at Nagarro from 2019 to 2021, where he applied data-driven methodologies to solve complex business problems. Before that, he served as a Teaching Assistant for a Machine Learning course at Coding Ninjas India in 2017. His experience spans various aspects of data science, including the implementation of innovative solutions such as a Probabilistic ID Unification platform and a Next Best Action Recommendation Framework.
Education and Expertise
Gurbaksh Sharma holds a Bachelor of Engineering in Computer Science from UIET, Punjab University. He further advanced his education by obtaining a Master of Technology (MTech) in Data Science and Engineering from the Birla Institute of Technology and Science, Pilani. His academic background provides a strong foundation for his expertise in Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM), as well as customer analytics.
Specialization in Customer Analytics
Gurbaksh Sharma specializes in customer analytics, focusing on key areas such as Customer Lifetime Value (CLTV), churn prediction, customer segmentation, and propensity scoring. His analytical skills enable businesses to understand customer behavior and optimize marketing strategies effectively. This specialization is crucial for organizations seeking to enhance customer engagement and retention.