Summary
Royer Torres is a Senior Data Scientist based in Hamburg with a decade of experience bridging particle physics and applied machine learning to solve high-impact business problems. He built production-ready systems across fraud detection, recommendations, and dynamic pricing, often leveraging graph neural networks and probabilistic models to capture relational patterns that traditional methods miss. His PhD and postdoctoral work on the ATLAS experiment gave him deep expertise in large-scale data processing, advanced statistical inference, and novel two-stage ML pipelines that were adopted by major collaborations. At consumer-facing companies he translated that research rigor into real-time decisioning systems and automated moderation tools, demonstrating a rare ability to move from petabyte-scale science to product-focused engineering. Royer is particularly interested in representation learning and geometric deep learning, and consistently applies physics-inspired approaches to make models more robust and interpretable.
10 years of coding experience
8 years of employment as a software developer
Bachelor's degree Physics, Bachelor's degree Physics at National University of Engineering
Doctor of Philosophy (Ph.D.) Particle Physics and Astroparticles, Doctor of Philosophy (Ph.D.) Particle Physics and Astroparticles at Aix-Marseille University
Master's degree Physics, Master's degree Physics at Universidade Federal do Rio de Janeiro
Spanish, English, Portuguese, French, German