Technical Leader AI4Life
I am currently helping launch Vibo, a learn-by-making platform where children build apps, games, music, and stories.
I am also contributing to a stock-trading bot competition platform and youth-focused AI education programs.
I am a product-minded technical leader with 12 years of experience at Amazon building data and machine-learning products that support organization-wide advertising decisions. I specialize in translating ambiguous, multi-stakeholder problem spaces into product vision, roadmaps, success metrics, and measurable business outcomes.
I have led large cross-functional programs spanning science, engineering, analytics, and partner teams. My experience includes driving Prime Day initiatives across more than 20 teams, setting priorities across five or more ML and engineering teams, and resolving delivery dependencies across organizations.
My background combines product strategy with deep technical foundations in machine learning, experimentation, large-scale data systems, SQL, Scala, Spark, AWS, and data modeling. I have delivered advertising data platforms processing billions of records and petabytes of daily throughput.
I am experienced in experimentation and A/B testing, including developing revenue-tracking mechanisms and performance-review frameworks that make experiment impact visible to leadership. I also define ML relevance metrics and partner with human-labeling teams to improve signal quality for downstream models.
I have led adoption, migration, privacy-compliance, and data-model redesign programs across dozens of teams. My written communication includes roadmaps, business requirements, working-backward documents, annual goals, status reports, and executive updates.
I am currently with AI4Life, where I am helping ship youth AI education programs, including Vibo, a learn-by-making platform for kids, and a stock-trading bot competition platform.
I am currently helping launch Vibo, a learn-by-making platform where children build apps, games, music, and stories.
I am also contributing to a stock-trading bot competition platform and youth-focused AI education programs.
Drove Prime Day programs across 20-25+ teams over multiple years, coordinating science, engineering, and partner vertical teams for the organization’s largest cross-functional delivery program. Owned product strategy and roadmap for Sponsored Brands brand data services, including brand metadata, relationship mappings, and query-understanding signals supporting relevance, retrieval, response-model, auction, and Nota teams.
Set vision, priorities, sequencing, and success criteria across five ML and engineering teams. Created organization-wide experimentation mechanisms, including Sponsored Brands A/B testing revenue tracking and performance reviews across 10+ teams, while driving adoption with Sponsored Products, Sponsored Brands Video, and Books teams. Defined brand-relevance metrics and partnered with human-labeling teams to improve annotation and ML signal quality.
Led delivery for a centralized advertising data lake serving 90% of advertising data needs, with more than 600 internal users, 100B+ records per day, and 5PB daily throughput. Led the Data Analytics and Insights team through sprint planning, request intake, roadmap ownership, and executive communication with SVP, VP, and director stakeholders.
Delivered automated daily data-availability and data-quality reporting and the Daily Global Flash advertising revenue report on Spark. Led the Diorama data-model redesign adopted by 50+ teams, the Ad Traffic project on AWS Redshift Spectrum, privacy-compliance reconstruction of advertising clicks across 14 tables and 55 teams, and the JIYU migration of 2,300+ SQL jobs from Oracle for 11 teams.
Built key advertising data pipelines, including more than 10 tables used for weekly business reviews, and contributed to the centralized Robot BI data platform serving analytical roles across the advertiser organization.
Built A/B testing data pipelines using Spark and Scala, with Tableau dashboards that enabled analysts to measure experiment outcomes through self-service reporting.
Master of Science, Executive Management of Technology
Completed a merit-based scholarship across four semesters. Coursework included information technology, cloud computing, economics of strategy, marketing, project management, accounting and finance, user experience, global innovation, and creativity. Attended the 2012 Entrepreneurship Program at NYU Stern School of Business.
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