Lena Levin

Product Manager

Seattle, WA, US

Operations Management

Analytics

Modeling

Go-to-market Strategy

Strategic Planning

SQL

Available for hire fromNegotiable

Contracts

Product & GTM Manager with expertise in Applied LLMs, semantic search, and personalization strategies. Specializing in experimentation roadmaps and e-commerce monetization with experience at Nike and Amazon.

I build products that change how millions of people search and shop. Over 11 years at Amazon and Nike, I've led cross-functional teams across 12 global markets—driving +150% conversion lifts, +33% search relevance gains, and +8% revenue growth. I turn ambiguity into strategy: aligning engineering, data science, and marketing around shared goals, then shipping fast (40% faster, actually). What I'm known for: making complex systems feel simple, running 50+ experiments without chaos, and building teams that deliver. Currently at Harvard, deepening my technical foundation in ML and data science.

Projects

Digital Coach - AI-powered pre-purchase discovery tool for Nike.com

Led 0-to-1 development and commercialization of Nike's AI shopping assistant. Digital Coach uses conversational AI to help customers discover products based on their needs, preferences, and use cases. My role: Defined product strategy, partnered with Data Science on ML models, designed pilot rollout with Sales and Success teams, and built feedback loops for iteration. Key results: +15% engagement on integrated surfaces +8% CTR improvement Integrated into search and product detail pages globally Cross-functional scope: Product, Data Science, Engineering, Design, Service Ops, and regional GTM teams across NA and EMEA.See More

Lifecycle Analytics Platform for Amazon Private Brands

Conceived and launched a predictive analytics platform enabling cohort segmentation and reactivation for Amazon's Private Brands business across 12 global markets. My role: Identified the gap in manual reporting workflows, defined product requirements, partnered with Data Science on predictive models, and drove adoption across marketing teams. Key results: Replaced fragmented manual reporting with self-service segmentation 80% improvement in marketer efficiency +5% AOV lift through targeted reactivation campaigns Accelerated decision-making across 12 markets Cross-functional scope: Product, Data Science, Engineering, Marketing, and regional teams across NA, EU, and APAC.See More

Semantic Search Rebuild - ML-powered search stack for Nike.com

Rebuilt Nike's search infrastructure using semantic ML models to improve intent recognition and product relevance across Nike.com and the Nike App. My role: Owned product strategy for the search overhaul, partnered with Data Science on model development, defined success metrics, and led A/B testing roadmap with 50+ concurrent experiments. Key results: +33% relevance improvement +10% CTR lift Replaced keyword-based matching with intent-driven semantic understanding Scaled globally across all Nike digital surfaces Cross-functional scope: Product, Data Science, Engineering, Search Ops, and Merchandising teams.See More

CS Agent - AI service automation for Nike post-purchase support

Led 0-to-1 launch of Nike's AI-powered customer service agent, automating post-purchase support across order status, returns, and common inquiries. My role: Defined product strategy and rollout plan, partnered with Data Science on ML containment and sentiment models, collaborated with Service Ops on pilot design, and built enablement and feedback loops with Success teams. Key results: +22% containment improvement +9 points CSAT increase in pilots Reduced agent workload on routine inquiries Built KPI frameworks for containment, CSAT, and latency tracking Cross-functional scope: Product, Data Science, Engineering, Service Ops, and regional GTM teams.See More

Automated Ad Auction Engine - Margin-aware advertising for Amazon Private Brands

Built an automated ad auction system that replaced manual sponsored product campaigns for Amazon's Private Brands, optimizing bids based on margin and performance signals. My role: Identified opportunity to automate ad spend, defined product requirements, partnered with Engineering on auction logic, and worked with Finance on margin modeling and impact measurement. Key results: Contributed hundreds of millions in incremental revenue Replaced manual campaign management with automated bidding Margin-aware optimization balanced profitability with visibility Scaled across Private Brands portfolio Cross-functional scope: Product, Engineering, Finance, Advertising, and Private Brands leadership.See More

Work History

Product & GTM Manager

Nike• Designed and executed global e-commerce strategies at Nike, focusing on search, recommendations, and AI-powered solutions. • Led AI/ML integrations that led to a significant revenue increase and enhanced customer engagement worldwide. • Unified multi-year product roadmaps to streamline collaboration across divisions and drive growth.

Product Management

AmazonJul 2014 - Sep 2021 • 7 yrs 3 mosDelivered transformative machine learning solutions for e-commerce, enhancing search relevance and driving revenue growth. Defined and executed product strategies, scaling adoption while mentoring teams toward operational excellence. Recognized for fostering innovation and collaboration, earning prestigious company awards.

Education

Harvard Extension School

Data Science, Artificial Intelligence

Ludwig-Maximilians-Universität München

BA, Statistics and Communications

University of London

MBA, International Business

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