My Background

Staff Data Scientist

I became a Data Scientist, a Consultant, and an Instructor after a decade in sales and business leadership. You can read the whole story in the blog page.

My last boss called me a force-multiplier for Data Science Application Deliveries, and I enjoy being able to translate my technical experience into architecting and driving larger projects. I made the biggest impact over the last year of my career by designing technical solutions, building project plans into Kan-Ban or Agile project overviews (PMO's), and leading the team through stand-ups and trade-off meetings so that our team could collectively execute on these solutions.

Over the next 1-5 years I see myself continuing to work as a project manager and a leader in data science and AI applications. I will contribute fewer individual technical pieces as time goes on, and I would like to contribute to both model creation and iteration, and to MLOps and CI/CD deployments before I take my hands off the keys.

The Longer Story

My background in sales and business management informs every action that I take as I pursue projects in automated vehicles and outer space exploration. I completed a Data Science Fellowship in an Immersive boot camp through General Assembly in 2020 before teaching there for the next year and a half. I was fortunate to start my first ML internship at Cloud Brigade in February of 2020, which turned into a paid position at the end of that year. I feel very fortunate to have had the opportunity to work with Chris Miller and his fantastic team for two and a half years before moving to a larger consulting firm at Capgemini in 2022.

Working remotely at both Cloud Brigade and Capgemini opened up 10 hours a week when I didn’t have to commute. In this extra 10 hours, I founded a nonprofit where early-career tech professionals could build applications together in cross-functional teams and gain experience to help them get full-time employment at places like Microsoft, Google, IBM, and Terran Orbital just to name a few. Co-founding the project with a solid group, we managed to work with over 200 professionals in our first 3 years, with between 25-40 folks in any given trimester. We’re in a rebuilding period now, so excuse the looks of the sites if you check them out now, but they are safe. https://SpaceLab.space

When I joined Terran Orbital in the summer of 2023, I felt I had finally attained my ideal career. That role as a Senior Data Scientist allowed me to lead small teams of highly motivated peers and mentors on cross-functional projects that brought immediate impact to the company, and could affect positive changes to how we live our lives. I also got to work under my friend and mentor Valentino Constantinou, a former JPL Data Scientist and published journal paper writer, who taught me so much more about software engineering, github workflows, and the aerospace industry in general. He even added me as a co-author in his paper in the IEEE, Leveraging Deep Learning for High-Resolution Optical Satellite Imagery From Low-Cost Small Satellite Platforms https://ieeexplore.ieee.org/document/10436344. While I was promoted to Staff Engineer, Applied Data Scientist, in May of 2024, the company went through a tough period and had to lay off a large chunk of the workforce in August of 2024, myself included. I value all of my coworkers at Terran, and am constantly thankful for all of the enriching relationships that started there. LLAP!

My dream is to work on projects involving human spaceflight, farming in space or on regolith, the exploration and settlement of Mars and other planets and moons, or autonomous vehicles (both in space and on Terra). Working on a project that reduces urban traffic thus cleaning our air and helping us get home from work faster is equally rewarding. In fact, projects with positive environmental impact are a new area of deep interest for me.

In addition to extensive work in both Azure and GCP (both FedRamp-compliant GovCloud and regular civilian level), I have spent the bulk of my time in the AWS cloud computing environment over the last five or six years, even earning an AWS Machine Learning Specialty in 2021. We were using AWS DeepLens and AWS SageMaker to employ a Reinforcement Learning algorithm to solve a traffic control problem on local roadways at Cloud Brigade. When COVID-19 forced a hard pause on the RL Traffic project, we turned our attention to the virus and began working on an Unsupervised Learning model that employs the Kmeans algorithm to generate insights in the data that weren’t otherwise apparent. I’m happy to be working on automating and expanding on the COVID reporting and forecasting dashboard now using python’s django framework, and I am hopeful that it will help health professionals protect us now and see ways to better public health in general in the future.

Not to plug AWS but I originally spun up this website from scratch using AWS route 53 to establish the DNS connection in 2019. I used AWS Route53 to establish the url, created an EC2 instance, and used Cloud9 IDE to connect and design. I then coded out a front-end in HTML using VIM from the Cloud9 command line, and pushed the application live using Elastic Beanstalk. While this current iteration utilizes SquareSpace, the work that I’ve led at The Spacelab has been exclusively in the AWS cloud until at least Q3 of 2024.