Nashville Metropolitan Area
I started my career as an electrical engineer (hands-on with vehicle systems, troubleshooting prototypes on the factory floor). That gave me something most consumer researchers don’t have: I know how products get built. Over time, I kept moving closer to the customer. From engineering to product planning, to advanced strategy, shaping next-gen vehicles and translating customer needs into major investment decisions. Then into consumer insights, where I introduced AI-powered research methods that cut weeks out of the insight cycle and changed how teams made product decisions. Now I’m building what comes next: synthetic personas, digital twins, and automated AI workflows that let product teams pressure-test concepts with synthetic models so that when real respondents are recruited, the research is sharper and more focused. I work hands-on: prototyping with LLMs, designing prompt architectures, and building end-to-end research workflows that move from business question to deliverable without project-by-project handholding. I'm leading the integration of synthetic research across the organization (not just running projects but defining where and how these tools create the most value at each stage of product development). Having led traditional research is what lets me know where synthetics genuinely add value (and where they don’t). What drives me: closing the gap between when the business needs an answer and when research can deliver one. My focus now is fully on the AI product side; designing the tools and workflows that make research faster, cheaper, and more scalable.
Building and deploying synthetic research infrastructure for advanced product development. Designing the AI workflows, prompt architectures, and organizational processes that make synthetic consumer modeling repeatable and scalable across the department. - Translating business goals into researchable solutions: assessing each product question, selecting the right synthetic method, designing the project brief, and executing through LLM-based models integrated with proprietary data. - Designing and deploying synthetic personas and digital twins for product-specific projects, enabling teams to test concepts, screen ideas, and model consumer behavior before committing to traditional research. - Building end-to-end prompt architectures (defining variables, sequencing, flow, and technique) to create repeatable workflows that move from business question to deliverable without project-by-project handholding. - Writing Python scripts to transform and integrate proprietary datasets into synthetic research workflows, ensuring models reflect real customer and market data rather than generic outputs. - Applying synthetic methods across the product development lifecycle, matching the right technique (if any) to each stage: early concept and message evaluation, concept screening, segmentation enhancement, data augmentation for hard-to-reach audiences, personalized marketing modeling, and scenario planning. - Training and enabling the wider team to adopt synthetic research tools, helping colleagues understand when and where synthetics add genuine value to business decisions. - Defining the emerging playbook for synthetic research, determining which stages of product development benefit most from AI-driven methods and building repeatable processes to reduce reliance on one-off execution.
Driving market intelligence transformation through AI-enhanced research methodologies, virtual consumer modeling, and platform innovation. - Built targeted virtual cohorts / synthetic customers using LLMs, machine learning clustering algorithms, and proprietary data to validate market concepts. - Designed and executed AI-driven testing of marketing strategies and campaign ideas against generative AI personas. - Developed and deployed automated workflows to streamline process testing through virtual cohorts, reducing manual effort. - Leveraged Microsoft 365 Copilot to build practical AI agents that improved operational efficiency and productivity. - Applied data-driven experimentation and generative AI to accelerate insight generation and decision-making. - Led the development of AI-powered research platforms—including virtual consumer models, custom GPTs, and global intelligence dashboards—reducing research timelines by 68% and cutting development costs by over 50%. - Directed multi-source, AI-enhanced market intelligence initiatives across powertrain, connected services, and post-launch feedback, delivering faster, more actionable insights to inform product and feature strategy.
Led the modernization of research processes through innovative AI and digital platforms, delivering impactful consumer insights and advancing organizational capabilities. - Evaluated and implemented AI-powered platforms to expand & streamline research. - Selected and deployed usability testing tools to assess client websites and improve UX. - Integrated LLM-based consumer intelligence tools into research processes, enhancing efficiency and insight depth while delivering actionable client value. - Oversaw online research communities with 1,000+ members, moderating and extracting insights using Q software. - Conducted UX testing with digital tools, delivering recommendations to design, marketing, and engineering teams.
Identifying overarching market and customer trends to drive future product development for Nissan & Infiniti vehicles. Using customer insight to translate into key strategic advantages for next generation solutions that are used for to set direction for downstream functions (R&D, Design, M&S), ultimately helping to guide investment strategies with vehicle development budgets ranging from $300M to $1B+ • Conducted psychographic factor analyses to identify underlying ideas/concepts of clusters of individuals into distinguishable groups for targeting • Developed UX into a customer need that will serve as a strategic pillar for the brand • Identified key strategic advantage areas and tested potential executions with customers to set product “vision” by prioritizing customer need for product decisions • Managed & trained team on processes involving customer needs identification & research methodologies
Created next generation vehicle concepts – requiring forecasting skills, customer needs identification, product innovation execution & business case creation. Communicated future vision globally to R&D, Design, and M&S to execute for production. • Managed every future Core Model – largest volume/highest importance for North American region (Altima, Sentra, Rogue) – as well as company icons (Sports cars, EVs) • Created and proposed unique customer archetypes for the global company to strategically target to meet future trends • Identified key technology opportunities for Advanced Engineering to meet future customer needs • Part of core team responsible for designing and developed several best practices, along with the current team-oriented work structure and flexible schedule implementation (first in the company) • Leveraged by HR to help understand future trends and how it would affect the company’s recruiting, retention in the future • Led research in focus groups, clinics and ethnographies to identify customer motivations to be applied to future vehicle • Designed research to gain consumer insight to develop target customers • Led cross-regional team to enhance career development and tools for global function • Created new process to challenge vehicle implications by parallel industry deep dives and collaborations (CHOPs, CRS Suppliers, Industry Experts, HMI experts, Aging Experts, etc) • Created Safety Strategy for Cross Carline & Product Planning Teams
Challenged with reinvigorating 3rd Generation Nissan Murano. Created strong business case & product plan (forecasts, trims strategies, mix forecasts, and price positioning) to bring vehicle to market - proven to be successful as Murano volume has recovered and serves as a profit generator for the business. • Develop product strategy: positioning, competitiveness & life management • Led next generation program inception prior to production • Product Lifecycle management: minor change planning & execution. Develop grade strategy and mix, feature content, packaging, pen rates, pricing, and volume forecasting