• Directed a cross-functional team of 16 professionals to lead a comprehensive product development process redesign. Implemented agile methodologies such as weekly sprints and rigorous review mechanisms to enhance efficiency and collaboration across the organization.• Designed and implemented sophisticated deep learning models to enhance customer onboarding experience and fraud detection capabilities, utilizing anti-spoofing techniques, selfie authentication, and document verification protocols.• Implemented strategies resulted in a substantial decrease in the delinquency rate from 8% to 3.7%, generating annual cost savings of $350,000 in servicing expenses.• Led the full implementation of a third-party AI-driven conversational chatbot solution, Floatbot, achieving a significant 43% reduction in Time To Resolution (TTR) for customer queries. This implementation enhanced efficiency and improved customer satisfaction.• Implemented a Firebase-based in-app notification system, resulting in a 13% reduction in zero-day past due (DPD) cases, enhancing overall customer payment behavior and timeliness.

• Directed a cross-functional team of 28 professionals, including engineers, designers, and testers, to spearhead the development of cutting-edge deep-learning models customized for the Lenskart App, facilitating enhanced user experiences and innovative features.• Led the planning, execution, and rollout of sophisticated machine learning algorithms to predict face shape, age, gender, face width, and pupillary distance from images with an accuracy of 98%. Leveraged Django API initially and later transitioned to Flask for streamlined performance and scalability.• The resultant products delivered significant outcomes, including a notable reduction in the Return to Origin (RTO) rate stemming from size fitment issues, plummeting from 27% to 8%. Moreover, the initiatives led to a 5% enhancement in online customer engagement and an 8% surge in online sales, highlighting the effectiveness of our product strategies in driving customer satisfaction and business growth.• Implemented face comparison functionality within the profile-in-profile feature (adoption rate 14.71%), leveraging computer vision technology for seamless profile separation. This implementation led to a doubling of per-customer orders on a month-on-month basis, demonstrating the effectiveness of product enhancements in driving customer engagement and conversion rates.• Visual search product to recommend similar eyewear present within the input image.

Established a non-profit startup dedicated to improving educational opportunities for underprivileged children, successfully growing the team to over 100 committed members. Secured funding from reputable organizations including CRY India and the College Director to support our initiatives. Contributed to the positive transformation of over 500 underprivileged children by facilitating access to education and fostering their holistic development.

• Analyzed the operations process in order to find the major reasons of RTO (Return to the origin) rate increment.• Worked on Shopify platform and Facebook blueprint in order to understand the e-commerce business.Impact: Reduced RTO rate from 33% to 21% by implementing various solutions according to the issues.

• Primary research on understanding the situation of children in early childhood (0-6yrs).• Assessed the situation of children’s status based on health, nutrition and education.Impact: The prepared report helped CRY in solving the issues faced by children in Dakshinpuri and Sanjay Camp areas in South Delhi.