Statistician and data scientist · Mathematics, UNAM · Mexico City
I build statistical models that other people can check and rely on: explicit assumptions, honest uncertainty, and code anyone can rerun. My work spans credit risk and loan pricing, clinical trials, observational health studies, national surveys and government administrative data.
- Bayesian longitudinal models (Stan) and clinical-trial data for a clinical-epidemiology consultancy.
- Statistical analysis for clinical research at Hospital Infantil de México Federico Gómez.
- Earlier: classification models for Mexico's working population (STPS) and pipelines for national household surveys (INEGI).
- Teaching assistant in 13 courses at UNAM's Facultad de Ciencias, from multivariate statistics and machine learning to survival analysis. I teach Statistical Inference and Regression around real-data case studies (pedestrian crashes, mortgage pricing).
| Project | Question | Result |
|---|---|---|
| Mortgage credit risk · code | Why did 2006 mortgages default almost six times more than 2017 ones? 100,000 Freddie Mac loans followed for up to 20 years (Python, SQL). | About 86% of the gap is the economy, not the borrowers. Competing-risks survival (naive Kaplan-Meier nearly doubles the default probability), a Cox model validated out of time (ranking transfers, calibration does not), and a Monte Carlo of portfolio losses that matches the Basel capital formula, with importance sampling and MCMC. |
| Randomised trial: diet during cancer treatment · code | Does an anti-inflammatory diet beat the standard low-residue diet for women receiving chemoradiotherapy for cervical cancer? (Frontiers in Nutrition 2026) | I directed the statistical analysis of the trial: 136 women randomised, attrition handled with intention-to-treat and per-protocol models, multiple imputation (35 datasets) and mixed models. Complete response 70.7% vs 54.8% (RR 1.29, 95% CI 0.92–1.8). |
| Pedestrian crashes in Mexico City · code | Is someone hit by a car every 30 minutes at rush hour? Tested with two years of emergency-call records (C5). | Every 36.6 minutes (95% CI 34.6–38.8): the claim overstates the frequency by about 22%. Getting there meant catching three data traps: a window bias that passed every diagnostic, crashes confirmed twice, and seasonal heterogeneity. A negative binomial frequency GLM with exposure is then validated out of sample. |
| Do mortgage brokers charge more? · code | What sets the rate on a US mortgage? 46,190 loans originated in 2024. | Not the channel: brokers −0.5 bp vs retail (95% CI −1.9 to +0.9) for the same risk, while a FICO of 660–679 costs +23 bp. Nonparametric tests, regression diagnostics, ANCOVA and MANCOVA show brokers write larger, higher-LTV loans at the same rate; a raw comparison gets the correspondent gap backwards. |
| Quick count and survey estimation · code | How should 900 polling stations be sampled to estimate a national vote share, using all 163,666 stations of the 2021 election? | Stratifying by district gives a margin of error of ±0.87 points; concentrating the sample in 30 districts, ±3.9. The survey part reproduces INEGI's official housing estimates exactly. |
| Imputing counts with excess zeros · code | Which imputation model works best for a zero-inflated variable in 583,678 patient records? (BSc thesis) | Zero-inflated Poisson had the lowest error, but only because its imputations were too narrow: it kept about half of the true variance. |
| Maternal diet and congenital heart defects · code | Is a mother's combined B-vitamin intake associated with complex heart defects in her child? (Nutrients 2026) | Each unit of a PCA-based B-vitamin index: adjusted odds ratio 0.707 (95% CI 0.586–0.843). |
- Vilchis-Gil J, Gómez-Jiménez AM, et al. Maternal Dietary B-Complex Vitamin Pattern and Risk of Complex Congenital Heart Defects in a Mexican Population. Nutrients 2026; 18(16): 2693. doi:10.3390/nu18162693
- Luvián-Morales J, et al., Gómez-Jiménez AM, et al. Benefits of an anti-inflammatory diet compared to a low-residue diet during concurrent chemoradiation therapy for patients with locally advanced cervical cancer: a randomized clinical trial. Frontiers in Nutrition 2026. doi:10.3389/fnut.2026.1835417
Methods: credit risk (PD, competing risks, portfolio loss simulation) · generalised linear and mixed models · ANOVA/ANCOVA/MANCOVA · survival analysis · Bayesian models and MCMC · multiple imputation · survey sampling and complex designs · clinical-trial analysis · meta-analysis
Tools: R · Stan · SQL · Python · SAS · Git · Quarto · LaTeX