In my current role as a Data Scientist at Sixt R&D, I collaborate with the Core ML team to create and scale data-driven solutions that enhance the user experience and engagement on the platform. Some of my key achievements throughout all my roles include developing a multi-signal ML based recommendation system that increased the conversion rate of followership through recommendations by 35%, building a keyword intent classifier for the platform's search engine, using LSTM and other deep learning methods, and designing and scaling an NLP-based recommendation engine that leverages various AWS technologies and text embeddings based on Transformer/laBSE models. This engine generates recommendations for over one million creators on the platform, based on their profile and content similarity.I hold a B.Tech in Information Technology from Amity University, where I authored a book chapter on IGI Mhealth, and have multiple certifications in data science, machine learning, deep learning, artificial intelligence, and data visualization. I have also worked as an Associate Data Scientist at Great Learning, where I used predictive analytics to forecast company sales of new products with a 95% accuracy rate and analyzed product usage and customer sentiment using LDA topic modeling and LSTM. I am passionate about applying my skills and knowledge to solve real-world problems and create value for businesses and society. You can find my work on Github and connect with me on LinkedIn. Thank you for your time.