Experience
My work sits at the intersection of economics, machine learning, and decision-making. I moved from academic research in macroeconomics and firm dynamics into applied science roles focused on experimentation, forecasting, and high-stakes product and business decisions.
Recent Roles
Applied Scientist, LinkedIn
- Build and scale forecasting and causal inference systems for product and growth decisions
- Partner with cross-functional teams to evaluate downstream effects of features and strategy changes
- Translate model outputs into clear decision recommendations for leadership
Data Scientist / Applied Scientist, Amazon
- Developed experimentation and forecasting workflows in fast-paced operational environments
- Supported decisions related to growth, marketing effectiveness, and financial outcomes
- Operationalized modeling outputs into production decision processes
Earlier Research and Applied Roles
Quantitative Researcher, Geode Capital Management
- Worked on empirical asset-pricing and ESG-focused research in a quantitative investing setting
- Built and evaluated research signals using financial and alternative data
Research Associate, Boston University
- Contributed to research in economics and finance using large-scale text and structured datasets
- Worked on empirical analysis related to firm behavior, markets, and macro-financial questions
Teaching Fellow, Boston University, Universitat Pompeu Fabra, and Barcelona Graduate School of Economics
- Taught graduate and undergraduate macroeconomics, microeconomics, and quantitative methods
- Supported course delivery, student learning, and assessment across multiple economics programs
Academic Background
- Ph.D. in Economics, Boston University
- Earlier research focused on firm dynamics, macroeconomics, and related quantitative methods
Core Strengths
- Causal inference with experimental + observational data
- Forecasting infrastructure design and model integration
- Decision-focused communication with technical and business stakeholders