Bengaluru, Karnataka, India
Experienced in data analysis and machine learning, I am a proactive individual who thrives in dynamic, technology-driven environments. My journey includes working on projects in collaboration with the University of Central Florida (UCF), where I delved deep into data analysis, neural networks, and machine learning, using R to drive insights and predictions. One of my remarkable experiences includes contributing to the "Education 4.0" course, where I collaborated with renowned experts from Kansas University and UCF. This endeavor enriched my understanding of the evolving education landscape and the integration of technology in pedagogy. I had the opportunity to work on an intriguing project aimed at Anomaly Detection in Gas Turbines in partnership with the University of Central Florida. This project involved leveraging neural networks in R, further strengthening my expertise in predictive modeling and machine learning. In addition to my strong technical skills, I have a knack for web design. My creativity in this domain can be seen in the design of the website intecsol.org, a project I am proud to have led and executed. As I continue to navigate through the world of data and technology, I am eager to explore opportunities that will allow me to enhance my skills further, contribute to innovative projects, and make a meaningful impact in the field.
• Implemented an Image Segmentation YOLOv8-based model to optimize the Segmentation welding arc and measure its size • Trained and evaluated 5 potential YOLOv8 models on 6 parameters, on 2500+ custom label images to reach the solution • Application provides feedback as a graphic on the screen to change arc length, reducing welder training time by 25%
• Gained in-depth understanding of various stages of the design thinking process, including empathizing, designing, ideation, prototyping, and testing. • Acquired knowledge about the fundamental tech system architecture needed to develop and operate any feature or product. • Worked on a project focused on Spotify to address a significant customer issue: validated through user interviews and online surveys, ideated using mindmaps, prototyped with Figma mockups. • Developed an AI-based assistant feature for the product as a solution. Evaluated the project using metrics like acquisition, engagement, retention, and monetization, while identifying potential challenges.
• Interviewed 200+ traders to identify and understand the customer behaviour, feature needs and drivers for customers • Used Hotjar to analyse over 100 recorded user sessions to identify UX issues and improvement opportunities in the website • Drove 2 end-to-end product strategies to incorporate features based on business insights and customer feedback • Increased trial to subscription conversion rate by 23% MoM based on the implemented product strategies