Cecil Shea
Machine Learning Architect at Georgia IT Consulting, INC.
Tbilisi, Georgia
Summary
🤩
Rockstar🎓
Top SchoolCecil Shea is a Machine Learning Architect with eight years of experience building end-to-end data platforms and investigative analytics pipelines, currently based in Tbilisi. He designs and authors systems for data scraping, engineering, NLP, and predictive modeling with a focus on OSINT and social media signals, blending academic rigor with production-ready tooling. His background includes leading data investigations and teams at Transparency International and the OCCRP, where he turned hundreds of thousands of leaked records into award‑winning journalistic stories through bespoke network analysis and automation. Earlier roles at GEICO honed his expertise in enterprise predictive modeling, feature engineering, and communicating results to executives. An active contributor to open-source analysis tooling, he implemented new entity analyzers for the well-regarded Aleph project, adding IP and IBAN detection and unit tests. He pairs a strong mathematical foundation (M.A. in Mathematics) with practical skills in Python, Spark, and API-driven data enhancement to surface actionable intelligence from messy, real-world data.
8 years of coding experience
12 years of employment as a software developer
University of KansasB.S, Physics & Mathematics 2005, B.S, Physics & Mathematics 2005 at University of Kansas, Lawrence
Github Skills (8)
regular-expression10
python10
data-analysis10
searching9
osi9
api8
git8
api-design8
Programming languages (3)
Github contributions (5)
alephdata/aleph
Apr 2018 - Jun 2018
Search and browse documents and data; find the people and companies you look for.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 commits, 4 PRs, 4 pushes in 2 months
Contributions summary:Cecil's contributions primarily focused on implementing and extending data analysis functionalities within the Aleph data search and browse application. This involved the creation of new analyzers for identifying and extracting data entities, specifically IPv4, IPv6, and IBAN numbers. The user made changes across multiple files including the core `regex.py` for the analyzers, `document_tag.py` to define the types of entities, and `setup.py` to integrate the analyzers. They also incorporated unit testing within the code.
lookinvestigative-journalismpythondata-searchgraph-database
occrp/tech.occrp.org
Jun 2018 - Jun 2018
Blog and home page for the OCCRP technology team
Contributions:27 pushes, 2 branches in 12 days
home-page
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