Summary
Joan Serrano is a Senior Data Scientist with six years of experience applying advanced math and machine learning to real-world problems, currently solving data challenges in the mobile gaming industry at Socialpoint. With a PhD in Theoretical Reinforcement Learning and a background in physics, he bridges rigorous research—work on Lagrangian duality and LP approaches to MDPs—with practical deployment of bandits and RL for personalized user experiences. His trajectory spans academic research, industry internships, and product-focused roles, giving him a rare fluency in both constrained convex optimization theory and its production use cases. Based in Wuppertal and originally from Spain, Joan is driven by curiosity and continuous learning, routinely translating theoretical insights into measurable game metrics and retention improvements. An often-overlooked strength is his experience connecting statistical social network analysis and forecasting work to behavioral modeling, enriching his approach to player-centric analytics.
6 years of coding experience
3 years of employment as a software developer
Bachelor of Science (B.Sc.), Física, 7.83, Bachelor of Science (B.Sc.), Física, 7.83 at Universitat Autònoma de Barcelona
Doctor of Philosophy - PhD, Theoretical Reinforcement Learning, Excellent with Cum Laude, Doctor of Philosophy - PhD, Theoretical Reinforcement Learning, Excellent with Cum Laude at Universitat Pompeu Fabra
Spanish, Catalan, English