Work

Building AI from
prototype to production.

10+ years shipping AI-powered products, ML systems, and experimentation platforms across Microsoft, Google, Pinterest, Netflix, and Meta.

Microsoft · Fabric RTI Mar 2025 – Present AI Products

Senior Staff Applied Scientist

Leading AI product development for Microsoft Fabric's Real-Time Intelligence platform.

  • Built three AI products from zero to one: an anomaly detection system for streaming data, an LLM-powered operations agent, and an automated operational discovery engine.
  • Designed reward signals and evaluation frameworks for agentic systems — including auto-raters, responsible AI assessments, and continuous quality measurement that informed fine-tuning strategies.
  • Hands-on across the full stack: wrote the core ML pipelines, agent orchestration, benchmarking engines, and production inference code.
LLM Agents Reward Modeling Evaluation Anomaly Detection Azure
Google · Gmail Sep 2023 – Mar 2025 GenAI Evaluation

Staff Data Scientist

Led AI/ML strategy and built evaluation infrastructure for Gmail's Growth and Premium products.

  • Designed and built the evaluation framework for GenAI products — connecting model performance to user engagement and surfacing highest-impact investment areas.
  • Created Gmail's growth metrics framework, which became the foundation for product investment decisions across the organization.
  • Established experimentation culture from the ground up — enabling the team to scale from a handful of experiments per year to 10–20.
GenAI Evaluation Metrics Experimentation GCP
Pinterest · Infrastructure Jun 2022 – Sep 2023 Team Building

Staff Data Science Manager

Founded the Infrastructure Data Science & Engineering team.

  • Built a team from 0 to 6, establishing Pinterest's first dedicated function for infrastructure intelligence and ML-driven optimization on AWS.
  • Developed capacity forecasting models and cost optimization strategies that drove global efficiency across Pinterest's compute fleet.
  • Designed cost attribution models that allocated infrastructure spend to VP-level organizations, driving accountability across engineering leadership.
Team Building Forecasting Cost Optimization AWS
Netflix · Customer Service Oct 2020 – Jun 2022 ML Systems

Senior Data Scientist

Designed and implemented ML systems for capacity planning, experimentation, and Quality of Experience optimization.

  • Built end-to-end capacity forecasting in Python — from data pipeline to model training to production deployment — directly influencing strategic hiring decisions.
  • Designed an experimentation framework using quasi-experiments and causal inference, with safeguards ensuring no adverse impact on agent performance.
  • Created an ML system to identify underserved customer cohorts, leading to product changes with estimated impact of $MM/year.
Causal Inference Experimentation Forecasting Python
Meta · Infrastructure Jan 2018 – Oct 2020 Production ML

Senior Data Scientist

Tech lead for infrastructure forecasting. Hands-on across the full stack in Python.

  • Re-architected the production forecasting system — built scalable pipelines, continuous monitoring, and dashboards serving capacity planning teams company-wide.
  • Partnered with software engineers to implement approximate query techniques on a petabyte-scale data warehouse, reducing compute and storage footprint.
  • Built models to estimate infrastructure ROI for ads systems, and organized a company-wide forecasting summit to establish best practices across Meta.
Production ML Infrastructure Forecasting Petabyte-Scale

Earlier career

Before Big Tech, I worked as a Statistical Analyst in Risk Management, a Statistical Consultant at Auburn University, and a Graduate Teaching Assistant — building the mathematical foundations that inform everything I build today.