About Me.

This is where I talk about me — mostly in regards to my career.

My name is Jeff Laiosa. Although “Jeffrey” is my given name, only friends call me that when trying to rile me up. And if my last name sounds as if I must be embroiled in some 100-year old vendetta, I promise that is not the case. It is just the name of my ancestors who left the fields to board a boat in promise of a brighter future.

Education

East Carolina University

I received my undergraduate degree in Computer Science from East Carolina University. Initially, I began in the School of Art & Design and then changed majors to computer science as engineering was a better fit for me. I found that I really liked constructing programs through abstraction to solve problems. It was here I studied analysis of algorithms, object oriented design and software engineering using languages: C/C++ and Java. Albeit I do not use those language anymore, I learned about how to design software components and perseverance.

MITx

Currently pursuing a MicroMasters® Program in Statistics and Data Science from MIT. Consisting of four core courses developed by faculty at MIT’s Institute for Data, Systems, and Society (IDSS), this program teaches the foundations of data science, statistics, and machine learning. During the courses so far I have implemented solutions for clustering, classification, recommender systems and probabilistic modeling.

Work Experience

North Carolina State University

I began building web applications at North Carolina State University in 2004. Developed primarily solutions in the LAMP stack (Linux, Apache, MySQL, PHP) and deployed them onto university hosts. Performed database normalizationI used frameworks (e.g., CodeIgniter) and custom Wordpress themes for most of the work. Our team built web templates for university departments so they had an easier time staying on brand. In addition, we championed Git workflows for web content editors and usability studies to understand how users interacted with our content.

Deutsche Bank

As a UI Prototyper embedded on a UX team, I built prototypes and design assets for engineering teams. In comparison to what I was doing previously, this role was 100% front-end. This allowed me to focus on Javascript, HTML and CSS — all of which were undergoing drastic changes at the time. It was here that I gained experience in agile software development and the software development lifecycle. I also began seriously developing my Javascript skills. While the engineering teams worked in Java/GWT, my team developed and tested components separately. We also developed style guides and bundled UI assets for engineering teams to use.

Interactive Intelligence

I stayed at the bank for about two years until I was contacted by a recruiter with an interesting position working as a software engineer developing a new cloud product called PureCloud in the telecommunications and customer service space. This was a highly robust product and was my introduction to cloud services (AWS). We developed the application in Ember.js and unit-tested all of our components. I worked extensively with cloud architects, automation engineers and designers to build the application. Focused on optimization, internationalization, accessibility and cross-browser compatibility.

Opto Wealth

After working in industry for a while, I decided to start my own company. I had a lot of ideas and the big one I wanted to pursue was the “Google Finance for value investors”. No one at that time had really harnessed the mountains of data that are publicly disclosed in financial statements every day. These documents contain not only the income and balance sheets, but also tons of information about the brands, operations, risks and the executives/advisors. Reading these statements revealed all sorts of insights and raised many fascinating questions.

So, I set out to build services that could collect, parse and analyze these data. But I ran into a problem. Rudimentary parsing techniques (e.g., regular expressions) were not working well as they did not generalize to the large disparities in document formatting. At that point I knew a little bit about machine learning, but not enough.

While it would have been nice to just drop everything and get an advanced degree, it was simply not practical at that time. So I did what a typical engineer would do: I hit the books and took a course on Machine Learning and AI. The first one being Andrew Ng’s Stanford course @ Coursera. The applications of mathematics applied to more recent optimization algorithms blew my mind.