Apr 2024 – May 2026 · 2 yrs 1 mo

• 1. Leading a team of 5 analysts across restaurant growth and experience charters to drive platform growth and empower restaurants through self-serve tools.
• 2. Owned project management, sprint planning and hands-on analytics delivery in a fast-paced product environment.
• 3. Built scalable restaurant insights platform comprising 5 Power BI dashboards and data pipelines powering the Swiggy restaurant app to enable restaurants with actionable insights on growth, menu quality, expansion opportunities and operational excellence.
• 4. Developed a multi-class text classification model to tag restaurant cuisine enabling cuisine-level benchmarking and insight generation.
• 5. Led multiple product launches end-to-end including instrumentation requirements, GTM strategy, success metrics and post-launch evaluation ( AM App, Virtual Growth Manager, Restaurant Ratings Logic).
• 6. Solved complex business problems such as Rx spend optimization, LM RCA framework and FVO optimization.

Dec 2021 – Mar 2024 · 2 yrs 3 mos

• 1. Worked as an individual contributor partnering closely with key business stakeholders in the restaurant growth team to solve complex, high-impact problems.
• 2. Built Restaurant Goodness Score to holistically evaluate restaurant performance across platform impact, customer experience, and profitability enabling targeted improvement actions.
• 3. Designed a Quality of Supply (QoS) framework using regression model to quantify the impact of restaurant side attributes on order volume and derive QoS scores at a hyper-local level.
• 4. Developed an M2C attribution framework to understand drivers of menu-to-cart conversion, supporting weekly business planning and target setting.
• 5. Worked on multiple product initiatives including Self-Serve Ads & Discounts, Self-Delivery and Finance Reporting in the partner app.

Nov 2018 – Dec 2021 · 3 yrs 1 mo · Bengaluru Area, India

• 1. Worked with Sr Vice President of a leading US-based CPG manufacturer to design a performance assessment framework for newly launched innovations.
• 2. Identified key sales drivers for new product launches through deep exploratory data analysis across sales trends, pricing, promotions, distribution, and A&M spends.
• 3. Built a best-fit linear regression model in R to quantify the impact of these drivers on sales, enabling data-driven budget allocation and launch optimization decisions.
• 4. Led a team of three decision scientists to build a scalable asset health monitoring and preventive maintenance optimization solution for a US-based oil and gas major.
• 5. Designed a reliability analytics framework tracking critical asset health metrics and developed survival regression models to forecast time-to-failure using historical equipment data.
• 6. Delivered the solution end-to-end on Azure, with a Python-based web application to enable easy access and adoption by business users.