Daniela Mendirichaga

Research Analyst

Global Development Policy Center, Boston University

May 2022 – September 2025

Three years on a multi-project collaboration with Heineken, a global market leader in alcoholic beverages.

• Cross-market experiments across 5 countries. Advertising, product placement and pricing interventions. Treatments moved the target KPI by 8 to 20 pp. Where real data was infeasible, I engineered LLM-generated, census-anchored synthetic datasets and built the price-sensitivity models on those.
• Reproducible Python/R pipelines. Cleaning, feature engineering, modeling, evaluation. High-dimensional behavioral, transactional, survey and experimental data. This is what let the modeling scale across 10+ treatments and kept cross-functional reporting fast.
• Advised senior Heineken leadership. Presented and defended experimental findings that shaped product, pricing and behavioral strategy. Coordinated reporting, data access and paper co-authorship across the IDB, BIT and OECD.

Research Assistant and Teaching Assistant

Economics Department, Anahuac University

Mexico City · August 2020 – May 2022

Causal inference & structural econometrics

• Demand and supply in the pizza market. Structural demand and pricing model in pyblp; IVs isolate the causal price effect.
• Dynamic pricing replication. Reproduced a published storable-goods model: volume discounts plus inter-temporal pricing lift profits 10%.
• Data centers and electricity prices. County-panel OLS testing data-center activity against US residential electricity prices.

Discrete choice and willingness to pay

• Camping park demand. Mixed logit (xlogit) recovering willingness to pay for amenities and travel time.
• Transportation mode choice. Multinomial logit coded from scratch via MLE, benchmarked against logit and LPM.

Predictive modeling

• Airbnb booking probability, Los Angeles. End-to-end pipeline benchmarking L1-logistic against XGBoost under a chronological split.
• Used-car prices. Trees and XGBoost against an OLS/Ridge/LASSO baseline, compared out-of-sample.
• Telecom churn. Logistic regression written from scratch, with bootstrap uncertainty estimates.

Forecasting

• US construction employment. Prophet forecasts with seasonality and holidays, validated by rolling time-series cross-validation.

Master of Quantitative Economics (STEM)

University of California, Los Angeles

Los Angeles, CA · September 2025 – December 2026

• AI Agents Workshop: agents, tool calling, RAG and document intelligence, multi-agent orchestration, MCP-based deployment.
• Advanced tracks in Econometrics and Machine Learning. Selective; top third of the cohort.
• Departmental Merit Award, UCLA Economics.
• Coursework: Machine Learning & Big Data for Economists; Advanced Machine Learning for Economists; Advanced Econometrics; Empirical and Mathematical Industrial Organization (the latter a PhD course); SQL & Data Management.

B.S. in Economics

Anahuac University

Mexico City · August 2017 – May 2022

• Thesis: quantifying the tax-collection effects of Mexico's criminal-fiscal reform before its repeal. Modeled firm-level transaction behavior and estimated policy impact with difference-in-differences.
• Fellowship, Universidad Anahuac.
• Special Selection Award, CitiBanamex National Economics Prize nominee (2022).