Beginning

My journey to becoming a Quantitative Developer, started in 2018. I was fresh out of undergrad and had just started my career as a Performance Analyst. As a Performance Analyst, my job was to calculate many of the ex-post metrics we reported to clients as well as to the investment team for their post-mortem reviews. To my surprise, this was a rather tedious and manual process with many bottlenecks. Luckily for me, my ECON 482 class (Econometrics Theory) introduced me to my first programming language, R. I knew that I could use R to systematize many of our processes. So I got to work and within weeks, we were seeing exponential improvements in efficiency as well as significant reduction in manual errors.

Building what ended up being such powerful scripts for our team felt like magic and I was immediately hooked. I was so excited to learn about programming as knew I was just scratching the surface of what technology could do. So energized by this excitement (and a lot of naivety), I jumped into the deep-end and set out to conquer programming (whatever that meant).

Quant

I knew I needed to change roles if I wanted to get closer to building the technology. Luckily for me, my previous work was noticed (and I'd like to think admired) by those in power at the firm. So long-story short, in 2020 I was given the opportunity to become a 'Quant'.

As a Quant, I began to transition from a 'spaghetti-coder' to building smarter more effective tools and programs. I was given a project to work on an MS SQL Server database--from which, I learned SQL. I was also given a project to systematize more processes--from which, I decided to make the switch from R and began learning Python (more was happening in the Python community and I wanted to ride the bigger wave). I was writing smarter, learning about design patterns, managing environments, object oriented programming, and more.

But after a couple years of this continuous growth, I felt I was starting to hit a ceiling and plateau. This scared me. I was way too early in my career to be slowing down. So I began working on and gravitating towards research projects as this is where I believed the smartest work was happening. From which, I made the conclusion: if I could surround myself with these incredibly brilliant people, I would naturally learn the most (by way of osmosis or something like that). And if nothing else, the work they were doing was simply more interesting than anything else I was exposed to.

Proper Engineer

In 2022, I was given the dream opportunity and I joined a Systematic Multi-Asset Research Team as an Engineer. I also got to move away from Seattle and enjoy a sunny winter for once in beautiful San Francisco--cherry on top!

As a Research Engineer, my job was mainly to maintain and build the infrastructure that made our business 'Systematic'. This required working with a lot of different technologies:

• I got to work with many different database technologies (SQL Server, ClickHouse, Mongo, ArcticDb) and was responsible for designing various schemas. From which I learned about compressing, normalizing, and serializing.
• I got to work on designing APIs to put an engine behind an idea (Python, Matlab, R). From which I continued to learn how to write better code (linting, testing, versioning).
• I got to build interactive dashboards to bring to life our ideas and their required monitoring for the PMs and trading teams (Streamlit, JS, CSS, HTML). From which I learned about front-end development and the client-server relationship.
• And with all of this, I got to build out orchestration and manage environments to support everything. I learned about about Windows, Linux, Docker, Docker-Compose, CI/CD, and much more.

In this role, everything clicked and I became a full-stack engineer.

To top it off, we were building something very exciting and still very new in the industry. We were building a scalable, fully customizable multi-asset platform where clients could come and choose their 'alpha blocks' (think legos) to fit their unique needs.

But in early 2025, there was a major change in the leadership at our boutique and the new direction of the firm did not include systematic (and therefore me).

What's Next?

I'm not sure what exactly lies ahead. But I'm excited. Right now is one of the most exciting times in tech with AI. Never before has a developer been so empowered to create and be productive. I'm reminded of the same feeling of magic back when I first started coding in 2018. And just like back then, I'll be jumping into the deep-end and conquering the power of AI (whatever that means).