India
As an Associate Architect – Data and AIoT at CloudThat, I design and implement scalable data flow architectures utilizing AWS services like Lambda, S3, and DynamoDB. I actively engage with clients to analyze their requirements, ensuring tailored solutions that align with their objectives. I bring expertise in natural language processing (NLP), data pipelines, and research and development. My prior experience at AutomationEdge involved developing NLP models, computer vision systems, and AI tools for RPA applications. I am committed to leveraging cutting-edge technologies to deliver impactful, data-driven solutions.
• Client Interaction: Engage with clients to thoroughly understand their project requirements and objectives, ensuring that all aspects of the solution align with their business needs and expectations. • Requirements Analysis: Analyse and document client requirements to create a clear and actionable plan for the development of data flow architectures. • Data Flow Architecture Design: Design and develop comprehensive data flow architectures using AWS, incorporating best practices for scalability, efficiency, and reliability. • Solution Implementation: Implement the designed architectures by leveraging various AWS services such as Lambda, S3, DynamoDB, and others, ensuring that the solutions are robust and scalable. • Performance Optimization: Continuously monitor and optimize the performance of implemented solutions, adjusting as needed to enhance efficiency and effectiveness. • Machine Learning Integration: Research and evaluate the latest advancements in machine learning technologies, incorporating relevant innovations into solutions to improve functionality and achieve project goals. • Technical Documentation: Prepare and maintain detailed technical documentation for all developed solutions, including architecture diagrams, implementation guides, and user manuals. • Collaboration and Communication: Collaborate with cross-functional teams, including developers, data scientists, and project managers, to ensure successful project delivery and client satisfaction.
• Developed multiple NLP models using transformers like RASA, BERT, and GPT for sentiment analysis, text classification, and topic modelling. • Collaborated with the RPA team to develop POCs for NLP and CV use cases, resulting in effective integration into the company’s product line. • Contributed to the development of a Computer Vision model for object detection using YOLO and Tensorflow Object Detection and the company’s document analysis product. • Implemented an end-to-end NLP cleaning and analysis pipeline for the ”DiscoveryEdge” product using Python and various NLP libraries. • Contributed to the development of internal data science tools and libraries to improve the efficiency of the team