Data Scientist & Statistician
Data Scientist & Statistician
I turn messy data into decisions people can act on.
I build analytics systems, statistical models, dashboards, and research workflows for teams that need clarity from complex data. My work spans computer vision analytics, market segmentation, predictive modeling, statistical validation, and data storytelling.

Currently
Data Scientist at meldCX
Analytics for computer vision products across retail, QSR, and banking use cases.
Quantitative Researcher
Researching quantitative and algorithmic trading strategies for crypto markets.
MS Statistics
Bayesian spatiotemporal modeling
Co-founder
Stat IQ research consulting
Quant Research
Algorithmic crypto trading
Builder
Python, R, SQL, dashboards
What I Do
Computer Vision Analytics
Transform raw detection events into client-facing metrics, KPI logic, dashboards, and insight narratives.
Statistical Modeling
Design rigorous methods for forecasting, segmentation, validation, experiments, and research-grade inference.
Dashboards & Decision Tools
Build interactive reporting workflows that connect technical analysis to operational and strategic decisions.
Research Consulting
Help teams shape research questions, sampling plans, survey designs, statistical tests, and stakeholder-ready reports.
Featured Work
Project
AD-GEnKS Adaptive MCMC
Implemented adaptive MCMC workflows for Bayesian dynamic spatiotemporal modeling, supporting probabilistic forecasting of solar radiation fields.
R Bayesian Modeling MCMC Spatiotemporal Forecasting
Research
COVID-19 Vaccine Sentiment Analysis
Developed deep learning sentiment models for Philippine vaccine discourse using scraped and labeled Twitter and Reddit data.
LSTM CNN Word2Vec Label Studio
Visual Portfolio
Data Visualization Portfolio
A curated collection of visual storytelling work across income inequality, vaccination rollout, climate patterns, voter demographics, and exploratory statistical graphics.
How I Can Help
I work best when the question is messy, the data is imperfect, and the output still needs to be useful for real decisions.
You have messy data
I design reliable metrics, clean analytical workflows, and validation checks.
You need a model
I build forecasting, segmentation, and predictive workflows with defensible evaluation.
You need stakeholder buy-in
I turn findings into dashboards, visual narratives, and decision-ready reports.
You need research rigor
I structure hypotheses, sampling plans, statistical tests, and validation studies.