California, United States
• Led development of AI-driven personalization features to optimize product discovery, increasing storefront
conversion rates by 19% across active merchants
• Defined roadmap for real-time recommendation systems leveraging customer behavior, purchase history, and
browsing signals across 5M+ users
• Partnered with ML and data teams to deploy recommendation models, improving click-through rates on
personalized content by 17%
• Designed experimentation frameworks (A/B testing) to validate personalization strategies, accelerating feature
iteration cycles by 30%
• Launched dynamic content modules (recommended products, bundles, upsell widgets), increasing average order
value (AOV) by 11%
• Collaborated with engineering to build scalable APIs supporting low-latency personalization (<150ms) across
storefronts
• Developed dashboards tracking engagement, conversion lift, retention, and revenue impact for personalized
experiences
• Worked with design and UX teams to ensure seamless integration of AI features into merchant storefronts
• Gathered merchant feedback to refine feature usability, improving adoption of personalization tools by 25%
• Influenced go-to-market strategy and product positioning, driving adoption of AI capabilities across SMB and midmarket merchants