Sławek Smyl is a Distinguished Data Scientist with over a decade of deep expertise in forecasting, blending statistical methods and neural networks to win top international competitions including M4 and IEEE CIF 2016. He has driven forecasting and capacity-optimization work at Walmart, Facebook, Uber and Microsoft, applying probabilistic programming (Stan, Pyro), dynamic neural frameworks (DyNet, PyTorch), and advanced simulation techniques. His research contributions include state-of-the-art time series algorithms that outperform published results on M3 data, several scientific papers, invited talks at ISF and KDD, and three software patents. Comfortable across systems and languages from Fortran to C#/Java and databases like Oracle/SQL Server, he pairs production-grade engineering with academic rigor. A multi-citizen (Poland, Australia, US green card) with degrees in physics and computer systems engineering, he uniquely combines legal studies and simulation expertise to tackle complex, real-world forecasting problems.
10 years of coding experience
23 years of employment as a software developer
Graduate Diploma, Legal Studies, Graduate Diploma, Legal Studies at UNSW Australia
Master's Degree, Physics, Master's Degree, Physics at Jagiellonian University
Master's Degree, Computer Systems Engineering, Information Technology, Master's Degree, Computer Systems Engineering, Information Technology at RMIT University
Contributions:7 commits, 6 pushes, 1 branch in 10 months
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