May 2024 – May 2025 · 1 yr · Menlo Park, CA · On-site

• 1. Launched a new recommendation model for Facebook Feed using Reinforcement Learning, resulting in increased user time spent and revenue. Led vision, strategy, and execution across ML, data science, and UX, collaborating with VP-level stakeholders.
• 2. Leveraged Large Language Models (LLMs) to enhance content understanding and improve user action prediction—boosting diversity, freshness, and relevance of the Feed. Delivered higher quality standards than other recommendation surfaces while reducing misinformation and societal harm.
• 3. Drove a 0.2% increase in user sessions and a 0.3% lift in revenue through ML-driven product enhancements, including improvements to heuristic-based and template-based recommendation models.
• 4. Partnered with the Central Integrity team during the 2024 election cycle to ensure fair ranking and responsible distribution of political content on the platform.

Mar 2022 – May 2024 · 2 yrs 2 mos · Seattle, Washington, United States

• Led a cross-functional team in product management, engineering, science, go-to-market, and data for Amazon Rekognition, a computer vision service with customizable models for image and video insights. Launched new features and enhanced existing ones, including liveness detection, face matching, eye gaze detection, occlusion detection, celebrity recognition, and image/video analysis.
• Key responsibilities:
• Collaborated with customers in FinTech, retail, eCommerce, and public sectors to gather feedback, understand pain points, identify needs, and prioritize product enhancements.
• Partnered with engineering to translate product requirements into technical specs, guiding development for timely, high-quality feature delivery.
• Expanded Amazon Rekognition to new regions and data centers.
• Authored blogs and white papers on Face Matching and Liveness Detection, focusing on responsible design and use.
• Worked with sales and business development to support customer engagements, provide product expertise, and ensure successful onboarding and adoption.

Jun 2020 – Mar 2022 · 1 yr 9 mos · Seattle, WA · On-site

• Led a diverse team comprising engineering, developer advocacy, product marketing, UX design, privacy, and legal professionals for the Apple App Store, used by XXXM users across 150+ countries. In close collaboration with premier app developers, we focused on ideating and creating innovative products from scratch, aimed at boosting user retention, enhancing lifetime value, and reducing involuntary churn.
• Key responsibilities:
• Oversaw Core Commerce and Payments experiences within Apple Media Products, including App Store, iTunes, Apple Music, iCloud, and Apple TV+, driving strategic initiatives to enhance user experiences.
• Spearheaded product strategy to mitigate involuntary churn, boost revenue retention for developers, and foster wider adoption of Apple Media Products.
• Developed a comprehensive product roadmap for an ML-powered notification engine, empowering subscribers with timely reminders about upcoming payments and relevant applications, including games.
• Onboarded new payment methods on App Store and negotiated better financial terms with payment processors, card issuers, and banks.

Apr 2016 – Aug 2019 · 3 yrs 4 mos · Mumbai Metropolitan Region

• Product Manager in Valuation Controllers Group (2018-2019)
• Quant Researcher in Interest Rates Derivatives Group (2016-2018)
• Leveraged machine learning techniques to analyze trades across multiple business units, unlocking significant capital reserve requirements.
• Led enhancements to pricing models with a daily transaction volume of high magnitude, conducting user interviews, designing experiments, developing MVPs, and creating launch communications.
• Defined the product roadmap for fair valuation of high-value trades, reducing recession risk exposure by a substantial amount.
• Defined product requirements for a product to evaluate risks on a fixed income portfolio worth billions during extreme market volatility, resulting in significant computational cost savings.

Jun 2013 – Apr 2016 · 2 yrs 10 mos · Bengaluru Area, India · On-site

• Securities Lending Supply Technology Team
• Developed predictive tools to anticipate demand and supply for G10 stock markets during dividend season, resulting in a significant reduction in trade slippage and an improvement in profits.
• Spearheaded the end-to-end rollout of an issue resolution system across multiple regions, successfully achieving full adoption. Directed virtual demos, solicited user feedback, and documented future scope for continuous improvement.
• Designed database upgrade for trade database, increasing processing speed by a substantial margin.