Hello!

Thanks for stopping by!

I figured I would take a moment to provide a bit of background on who I am and my path to starting the data hackr.

While I am part engineer, part entrepreneur, part data connoisseur, part MacGyver, part computer whisperer, I prefer to go by my self-proclaimed moniker: a data hackr.

It wasn’t always this way. I evolved into this unique breed of hominid through a series of career adventures, educational experiences, a general distaste for the status quo, and a problem knowing when it’s time to call it quits and just take the easy route.

The Early Years 

As a kid growing up in the Chicago area I was constantly exposed to sports. Some great (the Bulls in the 90’s) and others not so much (the Bears, Cubs, and Blackhawks). Nonetheless, these teams and my crazy supply of kid-powered energy had me outside playing all sorts of sports pretty much all of the time. School was a bit of an afterthought…

Although scholastics weren’t my first priority, extracurriculars were tops. I played the trumpet in just about every band you can think of during grade school and high school, and actually got pretty good at it. I continued playing in jazz bands throughout college and grad school.

Along with this musical itch, I loved working with my hands building gadgets and gizmos. This led me to take up model rocketry with a friend of mine and eventually led to me deciding I wanted to become an aerospace engineer. Funny how things work!

Becoming One With Corn

On my quest to become an aerospace engineer my first stop was Ames, IA. At some point during my freshman or sophomore year at Iowa State University (not sure exactly when) a switch turned on. I was into this whole “school thing” for the first time in my life and was like, “math and science are actually pretty sweet!” Credit to the professors and facilities at ISU.

On top of that, I was introduced to something called coding. I quickly realized that you could accomplish a whole bunch with this new tool and was very interested to learn more. Fortunately, my Dad was a very experienced programmer and did the majority of his work in the same programming language I was learning, FORTRAN. Yep.. FORTRAN..

Later in college my interests started to drift away from aerospace engineering and more into the fields of artificial intelligence and optimization. All it took was a class that taught us about genetic algorithms, and I was hooked.

Hotlanta

Being a Chicago native, I was nearly knocked over by the near-tropical Atlanta humidity the first time I stepped out of my car in early August. I felt like I would never need to drink another glass of water, it was so thick!

I had come to Georgia Tech to build on my knowledge of aerospace engineering, specifically in aircraft and spacecraft design. The research lab I joined did just that. What I didn’t realize until almost a full semester in was that the design techniques we were being taught at the lab relied heavily on machine learning (something that isn’t typically used in aerospace). How fortuitous!

With this new realization I decided to dedicate my research to developing technology to improve neural network fitting, combining my optimization background with this new (to me) machine learning technique.

During my time working as a graduate researcher I had the opportunity to do conceptual design work for hypersonic missiles, help commercial aircraft manufacturers optimize their designs, and assess the US ballistic missile defense system with the military.

Knowing that I wanted to eventually become an entrepreneur I joined the MBA program at Tech which opened the door to the field of finance. Naturally, I wanted to apply my machine learning know-how to predict the stock market, which ended up being my first job.

Startups, Startups, Startups…

While I did a short stint for Boeing’s advanced design group, Phantom Works, during grad school, after graduating I never worked in aerospace. I would have never predicted that..

Since grad school I’ve worked at a bunch of startups (6 in total) in a wide range of industries. From finance to fraud detection to cloud architectures, I’ve worked mostly as a data scientist, machine learning researcher, or more recently led research & data organizations for startups. If you want the whole list you can find it here.

Along the way I managed to secure 2 patents for fraud detection techniques I developed, and eventually decided to try my hand at this startup thing.

A Startup of My Own

With two other co-founders, I founded Previsio, a startup created to solve the glaring problem of access to financial planning tools across the US. It confused me that the people in most dire need of these services were the people least likely to get them (due to access, cost, or trust). We were dead set on solving this problem.

After 3 years of fundraising, prototyping, building, testing, and iterating, we had to close shop. Our small team and limited resources couldn’t iterate fast enough to make a product that people really truly wanted. We built some really cool technology that could automatically create personalized financial plans for just about anyone (pre-retirement) and adjust to their needs in real time. Unfortunately we weren’t able to package it in a way that gained traction.

I feel so fortunate and privileged to have had these experiences. A lot of tough (but valuable) lessons were learned, but that’s a topic for another time.

Freelancing

After wrapping up with Previsio, I was looking for something different. So I decided to start consulting as a freelance data scientist.

I was attracted to this way of life because it would allow me to have a bit more relaxed and flexible approach to my job while still allowing me to use the 10+ years of experience I had cultivated in data science and machine learning.

Working at startups takes a toll on you and, unless you are lucky enough to have one exit in spectacular fashion, your wallet. Lack of benefits, lower pay, and no retirement contributions or company matching make a big difference over the course of a decade.

Even though I still don’t have insurance or retirement matching, I’m able to scale up and down my work based on how much money I want to make (and the hours I’d like to put in).

It hasn’t been all rainbows and butterflies though. Business was slow to start out but has been steadily growing as I expand my network.

The Data Hackr

My assumption in starting The Data Hackr was that people would be interested in hearing what I had to say.. I guess we’ll see 🙂

My hopes are as follows.

For folks that are interested in the hacks and data projects that I do, that sharing them may inspire people to think differently about the world around them.

For folks that are in a similar position in their career, that sharing my experiences with freelancing might show them a different way.

And for folks that are looking to start or improve their skills in data science and machine learning, that sharing my perspective, techniques, and tools may help them advance in their careers.

That’s all I’ve got!

Welcome to the blog – glad you’re here!

-Scott