Hi, I’m Ruiz 👋🏼
And I’m someone who uses Data Science to help communities take meaningful climate action while spending my nights learning the statistics that makes these algorithms tick.
Over the past few years as a Data Analyst with the BC Public Service, I’ve built analytical tools that help government teams make data-driven decisions across various programs. My day-to-day involves developing Power BI dashboards using DAX and Power Query for data modelling, writing Python scripts to automate tasks with various data sources, and maintaining SQLite databases that support operational planning. For example during wildfire season, my work becomes particularly critical as I use the Google Earth Engine API to overlay satellite imagery and visualize fire perimeters on human-readable maps. The tools I’ve built help teams identify the infrastructure or communities which demand an immediate response and deployment of aid. The results of which have helped guide multi-million dollar decisions on resource deployment during some of BC’s worst fire seasons.
However, my day job is only part of the equation. I’m constantly upgrading my toolkit through self-guided learning in the areas of Machine Learning and Bayesian Statistics. Right now, I’m reading through Professor Richard McElreath’s Statistical Rethinking textbook, building on the PyMC community’s work by porting the R examples to Python, and publishing chapter summaries as Colab notebooks on GitHub. I then apply these techniques to problems within the climate space that I care deeply about. Some of these projects include using Bayesian methods to analyze Vancouver Island wolf population dynamics, building regression models to predict wildfire spread based on weather data, or engineering pipelines to compile the datasets needed for analysis. And luckily, my work and interests has led me towards the opportunity to collaborate with senior data scientists in BC’s wildfire service to further the impact I can have with my talents.
The same drive that once had me in the gym at 5am when I was playing collegiate basketball now fuels late-night debugging sessions and deep dives into probabilistic programming. I believe the best way to learn is by doing and by making those learnings public so others can build on them. The crux of all my activities is guided by my mission which simply is to make every experience a learning experience and to do my part in leaving the world in a better place.
Within my portfolio website I have a collection of tools, tutorials, and experiments I’ve built to hold myself accountable towards continuous self-improvement in this field while simultaneously inviting you to join me on my journey. You’ll find notebooks on Bayesian methods applied to conservation problems, wildfire analysis workflows, and other climate-related projects. Like me, my projects are continuously a work in progress but I hope you can find inspiration in them to use your skills and knowledge to tackle the defining challenges of our lifetime.
Feel free to browse through my projects and if you spot any collaboration opportunities or want to discuss applying ML to the climate emergency then I’d love to chat. Thank you for taking your valuable time to visit my website!
Talk soon ✌🏼