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Data Product Manager @ KPMG | UC Berkeley | 3+ years building enterprise data products leveraging B2B SaaS
I’m a Product Manager with 3+ years of experience leading cross-functional teams to build and launch user-centric, data-driven products at scale. I specialize in using my love for data to dictate product strategy, roadmap planning, stakeholder management, and agile product development across diverse domains spanning financial services, B2B data reporting tools, and data pipelines & automation.
Most recently, as a KPMG consultant at Capital Group, I led a data curation and automation initiative for $55B in Assets Under Management, cutting daily ETF performance reporting time by 94%. I also built 4 self-serve data solutions leveraging B2B SaaS tools, reducing $1.2M in annual engineering costs. Previously at Pfizer, I launched a performance tracking dashboard that evaluated LLM-generated summaries with 92% accuracy against key AI safety parameters.
I’m the founder of PingMeJobs, a B2C job alerts platform that monitors career pages and delivers personalized job notifications with minimal delay. I conducted 60+ user interviews to identify pain points and built the product from zero to one. Today, PingMeJobs serves 2500 daily active users, has sent over 100,000 alerts, and maintains a 61% email open rate and 9.1% click-through rate.
Beyond building products, I run a Medium blog on product management best practices, attracting 460 subscribers and 40,000+ views, where I share insights on user experience (UX), growth, and product leadership with a growing community of professionals.
- Data Product Manager Consultant at Capital Group ($2.2 trillion USD Assets Under Management). Own Data Modelling, Curation, and Reporting activities for Capital Group's ETF products - Collaborated with Data Platforms and Insights & Analytics team to develop SQL scripts in Databricks; automated ETF daily flows reporting resulting in ~25 hours of monthly time savings - Transitioned competitor fee comparison reporting from manual workflows in Excel to automated solutions powered by SQL and PowerBI leading to ~80 hours of monthly time savings.
- Built end-to-end job alert tool that scans company career pages and delivers personalized, real-time alerts - Conducted 60+ user interviews to identify gaps in job search workflows and validate product direction - Designed and launched MVP using low-code tools + custom scripts; scaled to 2,600+ users - Sent over 120,000 job alerts with 61% open rate and 9.1% click-through rate - Applied A/B Testing, user research, growth, and retention tactics to drive engagement - Featured on Product Hunt and received strong user feedback for relevance and speed of alerts
- Conducted in-depth ad-hoc analysis on Large Language Models (LLMs) responses, generating actionable insights to enhance product performance. - Utilized Python libraries and statistical techniques to assess key operational metrics such as toxicity, fairness, bias, and robustness, contributing to a scoping review on ethical evaluation in Generative AI. - Transformed complex algorithms into a suite of APIs by collaborating with developers - Provided product owners with a user-friendly documentation guide for assessing LLMs across varied business use cases.
Walmart Global Tech · Internship
Investigated trends in Net Promoter Score for Walmart's product for drivers - Spark Driver. Also, managed a cross functional collaboration with Driver Experience, Strategy and Operations Team to come up with actionable recommendations to improve NPS.
Courses : - INFO 290M. Lean/Agile Product Management - INFO 225. Managing in Information Intensive Companies - INFO 290. Product Design Studio - INFO 247. Information Visualization and Presentation - INFO 271B. Quantitive Research Methods - INFO 234. Information Technology Economics, Strategy, and Policy - INFO 206B. Introduction to Data Structure and Analytics
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