Work

Go to market

Frontier LLMs Agentic systems Generative AI

OpenAI is focused on bringing AGI to the world.

Principal Solution Architect

Enterprise systems Platform architecture Solution strategy

This role expanded me from applied machine learning into enterprise AI architecture, where technical credibility, systems thinking, and executive communication had to operate together.

• Worked across identity, knowledge, collaboration, support, and workflow platforms, deepening fluency in complex enterprise environments.
• Connected architecture detail to business value so buyers, operators, and technical teams could align on adoption.
• Built the bridge from modeling-centric work toward broader platform thinking, which now informs how I evaluate AI in the market.

Lead ML Solutions Engineer

Forecasting Signal engineering Explainability

PredictHQ was where I learned to pair rigorous forecasting work with customer-facing problem solving, turning models into something explainable, deployable, and commercially meaningful.

• Built end-to-end forecasting workflows spanning event data, feature generation, model evaluation, and performance improvement.
• Worked across APIs, data products, and technical enablement, widening my exposure beyond modeling alone.
• Established the habit of tying analytical sophistication to adoption, a through-line that carried into later architecture and GTM roles.

Product Lead for ML Forecasting

ML product Planning systems Operational fit

Leading product for machine learning forecasting in an operational setting pushed me to think beyond model quality and toward full decision systems: workflows, incentives, and planning realities.

• Helped turn research-grade forecasting into a product that could support real planning decisions under uncertainty.
• Worked across product, applied ML, experimentation, and supply chain context, broadening the range of technical and organizational platforms I could navigate.
• Added a systems lens that made later roles stronger: the best model is the one people can trust, operate, and learn from.

Insights & Data Science

Voice of customer Insight design Stakeholder context

Medallia grounded me in how organizations learn from customer and operational signals, and how analysis only matters when it changes the decisions people make.

• Translated qualitative and quantitative experience data into narratives, metrics, and decision support for teams across the business.
• Strengthened my ability to connect analytics, storytelling, and organizational context rather than treating data science as an isolated function.
• Set up the move into forecasting and product by sharpening judgment around evidence, usability, and cross-functional trust.

Global Investment Research

Data foundations Analytics systems Research modeling

This was the technical and analytical foundation: rigorous research support, data infrastructure, and the discipline of producing signals that other people could depend on.

• Built fluency in data warehousing, infrastructure, business intelligence, and predictive analysis within a high-accountability research environment.
• Learned how to structure messy information, maintain analytical rigor, and support decision-makers with trustworthy outputs.
• Created the baseline that every later role built on: strong data habits, clean thinking, and respect for the systems behind the story.