As a data scientist, I enjoy solving complex problems using optimization and deep learning techniques. I am currently pursuing my master's degree in data science at Rutgers University, where I am learning the latest tools and methods in the field. My most recent role was at Ola, where I applied my skills in optimization algorithms, Python, and machine learning to create innovative and cost-effective solutions for the company and the customers. For example, I designed and implemented a novel algorithm for pricing pertinent to Ola Cabs, using distance-based metrics to suggest the final price. I also worked on the ”Snap Community Pickup” project, where we used pickup and drop-off data of users to select geo-hash coordinates, an Ola feature that suggests pickup locations to consumers based on historical data. Additionally, I proposed and tested an algorithm for proposing drop addresses based on initial search queries to avoid Google’s drop recommendation service costs. In these projects, I contributed to the improvement of the customer experience, the reduction of the operational costs, and the enhancement of the competitive advantage of Ola. I am motivated by the opportunity to leverage data and technology to improve the lives of millions of people, and I aspire to join a team that shares this vision and values diversity and collaboration. I believe that I can bring a unique perspective and experience to the team, as I have worked on various domains and applications of data science, such as pricing, navigation, and 3D reconstruction. I am always eager to learn new skills and explore new challenges.