G'day!

I’m Dan, a Kiwi currently expanding my horizons in the United States. I’m pursuing a Master’s in Statistics at the University of Wyoming and am an aspiring data scientist. You can learn more about my journey in the section A Little About Me. Also, you can see a breakdown of this website’s content by tags here.

My passion for data science is backed by four years of experience in scientific programming, mathematical, and statistical modeling. I’m known among my peers for my ability in applying a wide range of modeling methodologies and distilling them into concise scientific reports that unveil meaningful insights.

My academic pursuits have been diverse yet focused. I hold a Master’s in Economics, and I’m on the verge of completing my second Master’s in Statistics. This strong theoretical foundation has been instrumental in my practical work as a data scientist. My hands-on experience includes roles such as a graduate researcher at the University of Wyoming’s Advanced Research Computing Center, an intern bioinformatician at the Wyoming Public Health Lab, and an intern data scientist at Western EcoSystems Technologies.

One of my current exciting projects involves collaborating with the Mayo Clinic and Argonne National Labs. Here, I’m contributing to the development of an AI-driven medical software engine, designed to predict the progression of colorectal cancer in patients. This project forms a part of my thesis work and is a significant step in my data science journey.

Curious about what to expect from my website? Take a look at my article on Metropolis-Hastings MCMC from Scratch ✨. And there’s more to come! Stay tuned for upcoming posts on diverse topics like TiDE Time series forecasting in Python, implementing K-means in C++ from scratch, exploring LLMs and the Llama2 API in Python, and crafting visualizations with D3.js.

At the core of my professional life is a deep-seated passion for working alongside domain experts. I enjoy helping them understand and apply the best modeling strategies for their specific challenges. I find this process to hone my own craft from having to apply my knowledge to new problems as well as an inherent richness in learning something new from a domain expert. Sharing knowledge, experiences and collectively overcoming obstacles is, for me, the essence of what makes this field so rewarding.

Cheers,
Dan