Thomas Feuerbach

Analytical thinker, seeking to combine cross-discipline interests in statistical data analytics, machine learning, and pipelining in the cloud to drive data-driven solutions and insights.

Skills

Education

2015 – 2019 Bachelor of Arts in Economics, Virginia Tech

• Minor: Statistics and Law

Work History

08/2024 - Present - Data Operations Lead, ECS Federal

• Support HPC (High Powered Computer) server builds and installations end-to-end (design, build, install, network, STIG, and administrate) for multiple customers in purpose-built computer vision enclaves.
• Develop and maintain servers (physical and virtual) and their data pipelines for various modalities of data coming in from a variety of sources.
• Trained YOLO models on data collected from a variety of UAV/USV platforms
• Design and developed agnostic internal tooling to visualize computer vision annotations on video files from a variety of labeling platforms using OpenCV and Flask.
• Mentored and trained junior engineers on best practices for data management, pipelining, and development of secure and clean software.
• Developed CI/CD processes for internally hosted GitLab.
• Developed internal Python packages for interacting with vendor APIs that ended up being adopted by the customer for their own use.

10/2022 – 08/2024 - Data Engineer, ECS Federal

• Collected and prepared various modalities of media and geospatial data on the Smart Sensor project to supply the DoD with an intelligent and autonomous aerial sensor.
• Developed, maintained, and improved data pipelining for large quantities of visual and geospatial data collected from MQ-9 cameras and sensors.
• Worked on a team that gathered requirements, designed, and then deployed enclaves for various vendors to develop models in as part of DoD CDAO's AI/ML Scaffolding initiative.
• Managed various Linux servers on-premises and in the cloud. Time in data centers building and provisioning hardware for buildouts.
• Supported various flight test events and military deployments.

10/2021 – 09/2022 - Data Scientist, ECS Federal

• Developed a flexible, serverless data pipeline with AWS to serve our customer’s evolving analytical and computer visualization needs. The pipeline routes images and metadata from a range of data sources into an Elastic stack paired with Dash for visualization and analysis. This has elevated the value of social media for analysis during wartime within the Pentagon, most recently with Ukraine.
• Used Python (PySpark, Pandas, Dash), SQL, JavaScript, Elasticsearch, and Bash to transform and visualize data across AWS, Palantir Foundry, and on-premises servers.
• Performed iterative, exploratory analysis on a mix of clean and “dirty” data to gather meaningful insights quickly for the customer.

07/2020 – 10/2021 - Junior Data Scientist, ECS Federal

• With extensive use of PySpark and SQL, used computer vision models and their output to develop an intelligence dataset and interface control document used to drive decisions at the Pentagon level, as well as further business development and contract acquisition.
• Provided insight, guidance and solutions to customer’s complex data problems using data engineering, data manipulation and machine learning strategies.
• Worked daily with AWS ETL jobs to develop a pipeline that takes advantage of an aggregate social media data set in conjunction w/ model outputs to visualize, monitor, and trigger advanced ML alerts on incoming data into an ELK stack (Elasticsearch, Kibana, Logstash).

2020 – 07/2020 - Applied Technology Analyst, ECS Federal

• Created a departmental tracker to monitor and provide visibility into the status of accounts during their creation process.
• Provisioned accounts on classified network.
• Technical writer for CI/CD best practices between ECS and the DoD customer.
• Coordinated meetings between the customer and the PM.