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Work Experience
Event Programmer Specialist
Ticketmaster•  May 2021 - December 2021
• Created concert layouts and arrangements from the ground up alongside carrying out event related bug fixes as part of a wider team, which was deployed on Ticketmaster website. Managed end-to-end event planning and execution, ensuring accurate programming, quality checks and coordination with internal teams and external clients within time-sensitive environments, while fostering teamwork, efficiency, and a commitment to exceptional service.
Machine Learning Data Analyst
Amazon•  September 2019 - May 2021
• Worked in a data science team to preprocess, orchestrate and maintain data pipeline for training the Alexa NLP model. Improved user engagement through buyer persona analysis, feature enhancement, and optimization. Created impactful convention documents, identified product gaps, and led the design of new features across cross-functional teams. • Created and deployed an unified platform through aggregating information across several company portals for Amazon employees to enable smooth transition of new hires into their roles. Initiated and led the development of a streamlined platform, enabling Amazon employees to access multiple internal links efficiently, resulting in a centralized and user-friendly solution that enhanced productivity and facilitated onboarding for new hires. Additionally, effectively managed a diverse team of 40+ associates in a cross-functional setting encompassing quality assurance management and production.
Education
Queen Mary and Westfield College, University of London
Mathematics, MS•  September 2022 - Present
Modules (not limited to) : Machine Learning, Python Programming, Computational Statistics with R, Financial data analysis, SAS Programming, Neural Network and Deep Learning. Projects : Decoding Art using Machine Learning : A CNN-based Approach to Predict Artists from the patterns of their Artworks. Created a CNN based approach to predict artists based on their artwork based on a large dataset of 50 artists and 2000 artworks provided by Kaggle. Used transfer learning and fine-tuning from ResNets and VGG16 models to achieve a validation set performance of 65% Thesis : Recommendation System : Music and Movie recommender systems using collaborative filtering on public datasets. The recommendation systems allows users to receive personalized recommendations based on their preferences and similarities with other users in the dataset. By leveraging collaborative filtering algorithms, such as user-based or item-based approaches, the system analyzes user behavior and ratings to identify patterns and make accurate recommendations, enhancing the discovery and selection process for music and movies.
West Bengal University of Technology, Kolkata
Civil Engineering, B.Tech•  June 2015 - July 2019
Modules (not limited to) : Physics, Mathematics, Engineering mechanics, Values and Ethics in Profession, Structural Analysis, Principles of management, Organizational Behavior.
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