Product Management Leader · Saint Paul, MN
Senior Product Leader with 15+ years driving multi-product strategy and digital transformation within complex B2B SaaS environments.
I am a Senior Product Leader with a track record of building AI-centric roadmaps and leading cross-functional teams—engineering, UX, and sales—toward measurable business outcomes in complex B2B SaaS environments.
My philosophy is simple: great products are human-centered by design. I bring together data intelligence, AI capabilities, and UX insight to inform product strategy that compounds in value over time.
Whether managing multi-million dollar P&Ls, scaling agentic workflows and RAG architectures, or coaching distributed teams, I operate at the intersection of strategy, technology, and human-centred design—delivering results that last.
My Human-Centered Product Framework
Elizabeth is a founding North Star Member of MN Women in AI, a community dedicated to advancing women's leadership in artificial intelligence across Minnesota. As an active voice in the local AI ecosystem, she brings her product and strategy expertise to conversations about ethical AI adoption, agentic workflows, and the future of human-centered technology. Her membership reflects a deep commitment to building an inclusive, innovation-led AI community in the Twin Cities.
Hands-on technical work applying machine learning, forecasting, and predictive modeling to real-world business problems — built in Python with Google Colab & Jupyter Notebook.
A collection of applied ML projects demonstrating forecasting and predictive modeling across multiple domains — from retail demand planning to weather prediction. Each notebook explores data ingestion, feature engineering, model selection, and evaluation, showcasing how data-driven forecasting can power smarter product and business decisions.
An agentic sub-workflow automation built in n8n that enables intelligent event discovery and delivery. The workflow is triggered by a parent AI agent, queries the Ticketmaster API in real time, processes and aggregates the results, then automatically delivers a curated event summary to a recipient via Gmail — a practical demonstration of multi-step agentic orchestration applied to a real-world use case.
A fully agentic conversational AI system built in n8n that orchestrates multi-step event discovery from a natural language chat interface. Powered by Google Gemini, the AI agent understands user intent, routes requests to the Ticketmaster Search sub-workflow, retains conversation context via memory, and automatically exports structured results to Google Sheets — demonstrating end-to-end agentic RAG and tool-use patterns in a real production workflow.
A Python-based dynamic pricing decision engine that moves beyond static markup. It uses a three-layer logic system — cost baseline, operational saturation surge, and competitive guardrail — to recommend real-time prices that protect margins while keeping kitchen throughput within safe operating limits.
Not everything AI requires an Agent. This project uses n8n (self-hosted in Docker) to automate a practical financial reporting workflow — no code, low-code. A manual trigger pulls transaction rows from Google Sheets via API, loops through them sequentially to safely handle rate-limiting, and posts the results directly to a Discord channel. Built-in evaluation nodes verify the workflow is behaving as expected, making this a clean, testable, and repeatable automation.