Sep 2024 – Feb 2025 · 5 mos · Remote · Remote

• As a Product Analyst at Swiggy, I serve as the analytics point of contact for the Instamart Product team. I lead data-driven initiatives aimed at increasing the platform's average order value (AOV), partnering closely with cross-functional teams to enhance user experience and business performance.
• My role spans the entire product lifecycle, from ideation and conceptualization to business intelligence analysis, and ultimately, feature scaling and full release. I leverage data insights to drive decisions that shape key product features.
• Some impactful projects I’ve worked on include:
• Filters on Instamart home screen: Improving user experience and product discoverability.
• Progressive discounts for churn management: Designing and optimizing discount structures to retain users.
• Easy Cart: Enabling users to create personalized carts via voice, scan, or text input.
• By turning data into actionable insights, I contribute to Swiggy’s mission of delivering the best customer experience while driving business growth.

Aug 2024 – Sep 2024 · 1 mo · Hyderabad, Telangana, India

Jan 2024 – Aug 2024 · 7 mos · Hyderabad, Telangana, India

• As an analyst on the Australia and New Zealand Marketplace team, I collaborate with various product and tech teams to monitor and test new products in the market. This collaboration aims to enhance the overall experience and improve trip-level economics for all three sides of the business: eater, merchant, and delivery partner.

Oct 2022 – Aug 2024 · 1 yr 10 mos · Hyderabad, Telangana, India

Jun 2021 – Jul 2022 · 1 yr 1 mo · Noida, Uttar Pradesh, India

• As a Business Intelligence (BI) professional, I enable companies to leverage new technologies like ANAPLAN for their financial planning and analysis. By collaborating closely with clients, I develop and implement these new models to streamline their financial processes and enhance decision-making capabilities.

May 2020 – Jul 2020 · 2 mos · Roorkee, Uttarakhand, India · Remote

• I had the opportunity to collaborate with Professor Ashwini Sharma from the Department of Chemical Engineering. Together, we focused on producing mathematical equations through Genetic Programming. This initiative was aimed at identifying the optimal environmental parameters for the pretreatment of algal biomass, with an overarching goal of enhancing the production of biomass as a 100% carbon-neutral energy resource.
• Additionally, I developed a forecasting model utilizing Long Short Term Memory (LSTM) networks. This model was specifically designed to predict the likelihood of algal bloom occurrences in Lake Erie, North America. I am proud to report that this model achieved a remarkable accuracy of 96%, demonstrating its efficacy and potential impact on environmental monitoring and management.

Dec 2019 – Jan 2020 · 1 mo · Chennai, Tamil Nadu, India · On-site

• I collaborated with Professor Shubrabta Dutta from the Department of Metallurgical Engineering to develop and implement a deep learning model for the accurate classification of steel microstructures. This project successfully led to the complete automation of microstructural classification, leveraging the advanced capabilities of convolutional neural networks (CNNs). Our efforts culminated in achieving an impressive 95% accuracy rate, significantly enhancing the efficiency and precision of the classification process.