Working for Rajasthan Royals(Indian Premier League) as a Applied Data Scientist.

> Experience of working with Instrumental(London based Media Tech business) for singers as Data Scientist, where my work was aligned towards building a system using generative AI which takes Singers Scouting and promotion information in a (pdf, docx file) extracting the required information from those business documents and automatically generating the pitches to be used for pitching their songs on the Spotify, Amazon Music, Deezer, Apple.> At FRTYFVE, I leverage data science and AI to manage artists, using strategies that maximize social media engagement to boost streams and listener growth. I developed and implemented a sophisticated bot system integrated with Slack, which provides real-time updates on artists' performance across various platforms and delivers personalized updates via generative AI through email and WhatsApp. This ensures our teams and labels stay informed and can take proactive measures to enhance our artists' success.Spotify Streams,Spotify Followers,Spotify Saves,Instagram/TikTok Followers,Instagram/TikTok Engagement Levels were tracking KPIs, I provide actionable insights that have significantly improved our artists' visibility and engagement. This data-driven approach has resulted in measurable increases in streaming numbers and follower growth, driving overall business success and establishing a scalable model for other labels to adopt.>Researched on areas to improve RAG performance and evaluate RAG pipelines using RAGAs. This work impacted several porfolios across the business mostly used in Edtech where it helped achieving optimal evaluation of answers provied by the students during the exams.>Designed a system which automatically finetunes the models output based on the human feedback received FTHF for Gpt-3.>Developed a neural network architecture for forgery detection which helps in detection of forgeries done on the sensitive documents like Passport, Aadhar Card etc if any sensitive Information is modified.

Deep Learning, Probabilistic Graphical Models, Reinforcement Learning