Stéphane Damolini is a Senior Data Scientist and MIT-trained engineer with 7+ years applying machine learning, numerical modeling, and automation to high-stakes engineering and travel domains. He builds and deploys production deep learning systems for time-series forecasting and price prediction at KAYAK while previously driving probabilistic risk modeling, finite-element tooling, and data automation that doubled revenue and saved six-figure costs in industrial settings. Comfortable across Python, PyTorch, Spark, Snowflake, Kafka and ML ops stacks, he blends rigorous civil/structural engineering foundations with practical software delivery. Notably, he has authored domain-specific packages and signal-processing tools that became company standards and commercial products, demonstrating a rare mix of research-grade modeling and production engineering. Based in Greater Boston, he thrives on optimizing complex systems and turning tedious workflows into scalable, auditable pipelines.
7 years of coding experience
16 years of employment as a software developer
Mathematics Physics Engineering, Mathematics Physics Engineering at Janson de Sailly
Master of Engineering Civil and Environmental Engineering - High Performance Structures, Master of Engineering Civil and Environmental Engineering - High Performance Structures at Massachusetts Institute of Technology
High School Diploma [Baccalauréat] magna cum laude Sciences, High School Diploma [Baccalauréat] magna cum laude Sciences at Notre Dame des Oiseaux
Master of Science in Civil Engineering and Construction [Diplôme d'Ingénieur\ Civil Engineering Structural Engineering, Master of Science in Civil Engineering and Construction [Diplôme d'Ingénieur\ Civil Engineering Structural Engineering at ESTP - Grande école d'ingénieurs de la construction
Contributions:10 commits, 9 pushes, 1 branch in 1 year 3 months
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