📍 Los Angeles Metropolitan Area
🇺🇸 Clearance: TS/SCI
Updated: 03-25-2024

  Vincent Clemson  


The Pennsylvania State University 2017 - B.S in Mathematics | Minor in Statistics


👋 Hi I’m Vince. I’ve traveled 9,000+ miles driving across the United States over the past few months 🚗💨
I blog about using open source tools to analyze & visualize geospatial data. Previously, I worked at Booz Allen where I conducted a study on NATO1 object detectors using commercial satellite imagery on the Bighorn AI edge kit team. Prior, I worked at Peraton for 5 years on a GEOINT2 performance modeling & simulation team, where I analyzed billions of records of transactional data on geospatial imagery stored by the NGA3 to help optimize the NSG4. Additionally, I conducted data driven remote sensing & astrodynamics analyses in support of the systems engineering & integration of the NTM5-L mission. Here, I promoted open source software development best practices and data science tooling usage in Python & R. I also managed my team’s government network GitLab & corporate GitHub organizations, which grew from 0 to 300+ repositories over my tenure.

What I’m interested in doing

Applying my skills in geospatial data science & engineering to collaborate on a team with individuals who are passionate about their mission. I enjoy contributing as a positively impacting team member.

Open Source Projects

Programming Skills

I have hands on expertise in using various Machine Learning, Data Analysis, Geospatial & Visualization Packages, Web Technologies (app frameworks & scraping tools), SSGs7, & Notebook / Computational Medium tools.
Below is a non-exhaustive high level list of the technologies that I’m working in.
Python, Conda/Mamba, Jupyter, numpy, pandas, Sphynx, Cookiecutter, SQL, JavaScript, Node.js, Bash, Zsh, tmux, VSCode, R, Quarto, R Markdown, GNU Make, GitHub Actions, Leafmap, Google Earth Engine, QGIS, GDAL

Career Path

AI Engineer – Booz Allen Hamilton – CTO

  • Conducted an independent statistical performance analysis for evaluating Preligens’ aircraft & building geospatial computer vision algorithm detector models 🛩🏘️
    (e.g. developed a Python module for querying web API against Maxar satellite imagery, leveraged polars for data engineering & conducting ETL, used {sf} & {terra} for spatial analysis, & Quarto to document results)
  • Designed & prototyped multiple iterations of a human performance dashboard for JSOC8 using Oura Ring soldier biometric performance data (e.g. R {flexdashboard}, PowerBI, & Tableau)

Systems Engineer – Peraton

Data science on the NGA’s enterprise systems engineering contract (NEE/SEIN)

  • Analyzed the majority of imagery product transactions sent across the IC (e.g. NRO9/NGA’s ground CONOPS10)
  • Wrangled large amounts of historical categorical, numerical, spatial, & temporal GEOINT metadata using extremely efficient in/out of memory tools (e.g. data.table, Apache Arrow, & Parquet file data lakes)
  • Designed ETLs to pull and join data from disparate sources (e.g. APIs, S3 buckets, and databases) into tidy datasets for analysis (e.g. tracked imagery transaction timelines from satellite tasking to processing / exploitation)
  • Designed, developed, & maintained dashboards, visualizations (plots & charts), & data lakes for reporting engineering performance statistics on satellite camera sensors, as well as military base / intelligence site comms
  • Conducted orbital mechanics analyses using ephemeris & simulators of an ABI11 satellite / ground sensor system
  • Prototyped, developed, & maintained modeling tools to conduct EDA on data to analyze patterns and trends (e.g. ggplot2, sf, Plotly, Matplotlib, Leaflet, Dash, Shiny, Docker, & Cloud Foundry)
  • Performed spatial relational/geometric operations on datasets to enrich feature sets (e.g. border regions)
  • Statistical analysis on the performance, sizing, & budgeting of NSG imagery & their driving relationships
    (e.g. linear trend models, bandwidth models, human-in-the-loop supervised/unsupervised EDA ML workflows)
  • Worked on a distributed team & operated in a cloud computing environment. Experience with building a cloud from the ground up, config management, & permissions (e.g. AWS, RStudio Server Pro, Unix/Linux, VPC)
  • Used reproducible computational mediums to conduct workflows (e.g. R Markdown, Jupyter notebook)

Application Developer Intern – JP Morgan Chase

  • Agile development team in JP’s Technology Analyst Program. Team of 6 interns built a full stack Java-Spring tool aggregating data for the planning & execution of the migration & decommissioning of legacy JPMC data center servers. Worked frontend & backend. Led role as Scrum Master.

Machine Learning Skills

Some topics I’ve dived into while integrating machine learning workflows onto NSG transactional log data.
Spatial Cross-Validation Techniques, Discrete Event Simulation, Generalized Linear Models, Ensemble Models, Unsupervised Learning, Principal Components Analysis, Clustering Techniques, Feature Selection
Other topics I’ve dived into through various ML workings. e.g. rebuilding Deep Learning with PyTorch.
CNNs (Convolutional Neural Networks), GANs (Generative Adversarial Networks), Gradient Descent, Regularization, Decision Boundary, One-vs-All Multiclass Classification, Backpropagation and Advanced Optimization techniques

  1. NATO - North Atlantic Treaty Organization ↩︎

  2. GEOINT - Geospatial Intelligence ↩︎

  3. NGA - National Geospatial-Intelligence Agency ↩︎

  4. NSG - National System for Geospatial-Intelligence ↩︎

  5. NTM - National Techinical Means ↩︎

  6. STAC - SpatioTemporal Asset Catalog ↩︎

  7. SSG - Static Site Generator ↩︎

  8. JSOC - Joint Special Operations Command ↩︎

  9. NRO - National Reconnaissance Office ↩︎

  10. CONOPS - Concept of Operations ↩︎

  11. ABI - Activity Based Intelligence ↩︎