Paolo Dragone
Quantitative Developer
London, England, United Arab Emirates
Summary
👤
Senior🎓
Top SchoolPaolo Dragone is a quantitative developer with 12 years of experience translating research into production-grade trading and ML systems across crypto, ad tech, and consumer platforms. He has designed profitable algorithmic strategies and built low-latency distributed data pipelines ingesting millions of events per hour using Kafka, BigQuery, and containerized AWS infrastructure. Previously he scaled recommendation and retrieval models at Twitter and developed multilingual deep learning solutions and statistical detectors at Criteo, blending rigorous research (PhD-level) with hands-on engineering. Paolo is comfortable owning end-to-end stacks—from model development to real-time deployment—and has a track record of improving system reliability and deployment velocity under production constraints. Based in London with international academic experience across Trondheim, Melbourne and Oslo, he brings a research-minded approach to pragmatic, high-throughput systems engineering.
12 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Università di TrentoMaster's Thesis Abroad, Master's Thesis Abroad at University of OsloMaster of Science - MS, Engineering in Computer Science, Master of Science - MS, Engineering in Computer Science at Sapienza Università di RomaThe University of Melbourne
English, Italian
Stackoverflow
939reputation
75kreached
4answers
25questions
Github Skills (17)
jinja210
minizinc10
sat-solver10
constraint-programming10
pipeline10
python9
machine-learning8
sat7
oauth6
primefaces6
asp-net-mvc6
facebook6
xercesc6
editor6
custom-events6
Programming languages (2)
Github contributions (5)
paolodragone/pymzn
May 2016 - Sep 2019
A Python wrapper for the MiniZinc tool pipeline.
Contributions:16 releases, 639 commits, 17 PRs in 3 years 3 months
pythonpipelinepython-wrappersat-solverminizinc
unitn-sml/pyconstruct
Mar 2018 - Aug 2019
Python library for declarative, constrained, structured-output prediction.
Contributions:2 releases, 283 commits, 84 pushes in 1 year 5 months
constraint-programmingjinja2machine-learningminizincstructured-prediction
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.