🇺🇸 United States Citizen who to Travel
📍 Global 🌎
📍 Global 🌎
Updated: 08-03-2026
Vincent Clemson
Pennsylvania State University 2017
↘️ Checkout my online portfolio ↙️
B.S. in Mathematics | Minor in Statistics
Subject Matter Expertise
Analytical systems engineer specializing in data analytics, AI evaluation, statistical modeling, and software development.
Expertise building data products across intelligence, geospatial, technology infrastructure, and space systems.
Focusing on transforming complex data into actionable insight.
Artificial Intelligence & Machine Learning
Computer Vision Spatial ML Deep Learning Model Evaluation Prompt Engineering
Technical Toolkit
Programming
Python R SQL JavaScript Git Shell
Geospatial Analysis
QGIS GDAL PostGIS Google Earth Engine Leaflet sf terra
Data Engineering
Apache Arrow polars pandas data.table ETL
Analytics & Visualization
Plotly ggplot2 Shiny Dash Quarto R Markdown
Career Background
AI Research & Independent Technical Development
Analytical engineering through AI evaluation, geospatial software development, mathematical computing, and communication. Built open-source software, published technical articles, and piloted 220 drone missions. Explored frontier LLMs1, AI-assisted documentary filmmaking, and cinematic geospatial visualization workflows while traveling across 25 countries.
AI Engineer – Booz Allen Hamilton – CTO
- Lead on the CTO2 & NGA3 leadership’s engineering study to evaluate frontier overhead imagery computer vision models.
- Designed analytical workflows for evaluating frontier computer vision models using thousands of satellite images, combining ETL, advanced spatial querying, statistical analysis, and reproducible reporting to drive R&D capability & prototyping.
- Connected Safran.AI’s aircraft & building state of the art object dection models to Booz Allen infrastructure. 🛩 🏘️ 🛰️ 🗺️
- Designed & prototyped multiple iterations of a human performance dashboard for the JSOC4 using Oura Ring soldier biometric performance data (e.g. R {flexdashboard}, PowerBI, & Tableau).
Systems Engineer – Peraton
- Data science, modeling and simulation, & analytics on the NGA’s Enterprise Systems Engineering contracts (NEE/SEIN)
- Worked extensively with large-scale GEOINT5 imagery metadata and operational workflows across the NGA and NRO6.
- Developed ETL pipelines, analytical dashboards, and reporting systems supporting imagery engineering and mission analytics. Pulled disparate data sources into tidy datasets (e.g. APIs, S3 buckets, and databases).
- Built statistical models and exploratory analyses to identify patterns, calculate performance metrics, and predict resource utilization across enterprise-scale systems. (e.g. linear trend, bandwidth, cloud budget, imagery storage percentile models, satellite camera sensors, imagery product usage, military base & intelligence site comms)
- Evaluated model performance using statistical techniques, defining metrics and interpreting results to guide decision making.
- Conducted orbital mechanics analyses using ephemeris & simulators of an ABI7 ISR8 satellite / ground sensor system.
- Prototyped, developed, & maintained modeling tools to conduct EDA on data for analyzing patterns, trends, & spatial/geometric relationships. (e.g. ggplot2, sf, Plotly, Matplotlib, Leaflet, Dash, Shiny, Docker, & Cloud Foundry)
- 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)
- Gathered analytics requirements from lead/chief engineers, as well as mentored team from juniors, peers, to leads on analytic capabilities in 1-on-1, open forum, & presentation environments.
Application Developer Intern – JP Morgan Chase
- Agile development team in JP’s Technology Analyst Program. Team of six 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.
Data Analytics Intern – IMG Learfield & Penn State Athletics
- Analyzed unstructured season ticket holder survey text data using NLP9 techniques in Python (e.g. tokenizers, collocations)
- Performed Decision Tree Modelling in R for finding trends between customers and ticket sale renewals
Projects on the Web
- Combining math & code into bite sized technical explanatory articles on my travel themed Project Euler listing
- Designed aesthetic & interactive web maps in R using ggplot2, JavaScript, & SVG
- Rapidly visualized natural disasters around the 🌍 by developing web map tools that dynamically tile satellite imagery from Maxar’s Open Data Program using STAC10 & Leafmap
- Developed & Deployed analytic Dash & {shiny} web apps in Python & R for NGA mission analysts to predict years of geospatial coverage of NTM Earth Observation Satellite Systems
- Built Spatial Machine Learning Models using {mlr3} in R to run within GitHub Actions
- Worked through all of Tomas Beuzen’s Deep Learning with PyTorch & ported it to render w/ nbdev & Quarto
- Improved dev & data science workflows by teaching engineers to version control their code using Git
- Created Quarto, R & RStudio CLI utility shims to handle multiple Quarto/R installations
- Started developing an R package, {leaflet.super}, to visualize big geospatial data with Leaflet & Arrow
- Built exploratory unsupervised clustering tools to drive insight from imagery analyst user activity data
- Military wartime border region behavior is of interest within the geospatial intelligence domain, so I built tools for analyzing satellite image distance to border regions & for creating new geometric border regions
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Quantifying size & types of collections (e.g different camera sensor modes) is critical in Earth observation satellite systems engineering, so I’ve built different analytical product mapping tools to help do so:
e.g. advanced Plotly map animations & interactive Leaflet htmlwidget heatmaps - I version control my MacOS dot-profile & config files for rapid dev/data-sci setup
Additional Technical Experience
Below is a non-exhaustive high level list of the technologies that I’m working in.
Python, Conda/Mamba, Jupyter, numpy, pandas, Docker, Kubernetes, SQL, JavaScript, Node.js, Bash, Zsh, tmux, VSCode, R, Quarto, R Markdown, AWS, Google Cloud, GitHub Actions, Leafmap, Google Earth Engine, QGIS, GDAL, PostGIS
Machine Learning Topics
Spatial Cross-Validation Techniques, Discrete Event Simulation, Generalized Linear Models, Ensemble Models, Unsupervised Learning, Principal Components Analysis, Clustering Techniques, Feature Selection
CNNs (Convolutional Neural Networks), GANs (Generative Adversarial Networks), Gradient Descent, Regularization, Decision Boundary, One-vs-All Multiclass Classification, Backpropagation and Advanced Optimization techniques
LLM - Large Language Models ↩︎
CTO - Chief Technology Office ↩︎
NGA - National Geospatial-Intelligence Agency ↩︎
JSOC - Joint Special Operations Command ↩︎
GEOINT - Geospatial Intelligence ↩︎
NRO - National Reconnaissance Office ↩︎
ABI - Activity Based Intelligence ↩︎
ISR - Intelligence Surveillance & Reconnaissance↩︎
NLP - Natural Language Processing↩︎
STAC - SpatioTemporal Asset Catalog ↩︎
SSG - Static Site Generator ↩︎