V S Manideep Vemula
About V S Manideep Vemula
V S Manideep Vemula is a Data Scientist Assistant Manager at LatentView Analytics in Hyderabad, India, where he focuses on refining pricing strategies and optimizing marketing spend. He holds a Bachelor's degree in Mechanical Engineering from SRM University and a Master's degree in Information Technology Project Management from St. Francis College.
Work at LatentView Analytics
V S Manideep Vemula has been serving as a Data Scientist Assistant Manager at LatentView Analytics since 2024. He works in a hybrid model from Hyderabad, Telangana, India. In this role, he focuses on refining pricing strategies and subscription plans through detailed analysis of Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLV). His efforts aim to maximize revenue and enhance donor engagement. Additionally, he specializes in market mix modeling, which aids in optimizing marketing spend and forecasting user acquisition, ultimately contributing to improved return on investment (ROI) and strategic planning.
Education and Expertise
V S Manideep Vemula holds a Bachelor of Technology in Mechanical Engineering from SRM University, where he studied from 2012 to 2016. He furthered his education by obtaining a Master's degree in Information Technology Project Management from St. Francis College, completing this program from 2023 to 2024. His academic background provides a solid foundation for his expertise in data science, particularly in areas such as market analysis, user segmentation, and content optimization.
Background
Prior to his current position, V S Manideep Vemula worked at Shell as a Data Scientist from 2020 to 2023. His role was remote and based in Chennai, Tamil Nadu, India. Before that, he was employed at Ganit Inc. as a Data Scientist for two years, from 2018 to 2020, in the Chennai Area. His diverse experience in data science roles has equipped him with a comprehensive skill set in analyzing viewer engagement, content performance, and user behavior.
Achievements
In his professional career, V S Manideep Vemula has implemented personalized content recommendation systems that utilize collaborative and content-based filtering algorithms. This initiative has significantly enhanced viewer engagement and retention. He also conducts thorough analyses of content performance across various genres, which aids in optimizing acquisition and scheduling based on viewer preferences. His work includes segmenting users by demographics and viewing behavior to support targeted marketing and content curation strategies.