I'm Alessandro Sanvito, a Software Engineer at Optiver in Amsterdam. I work in the Quantitative Volatility Strategies team, building systematic options strategies and the data infrastructure behind them.
Before Optiver, I was an AI Research Intern at Mercedes-Benz in Böblingen, where I researched neural scene representations for autonomous driving, from reconstructing scenes through fog to complete 3D human avatars from limited viewpoints. That work led to papers at ICCV and IEEE IV.
I hold dual master's degrees from KTH Royal Institute of Technology (ICT Innovation, Data Science) and Politecnico di Milano (Computer Science and Engineering, 110/110 cum laude).
What I work with
At Optiver I build baseline systematic strategies for new product groups and the data pipelines that feed them: Python, Spark, Polars, and DuckDB over 10+ TB of instrument-level data, plus ML model training on AWS. I work closely with quant researchers, who take those baselines and optimize them for alpha.
My ML background spans deep learning (PyTorch, TensorFlow) with a focus on computer vision and generative models, plus classical ML with scikit-learn, CatBoost, and XGBoost.