Quant - Mathematician

At Oddin.gg, we don’t just follow trends—we forge them. As the fastest-growing tech company in Central Europe (Deloitte Fast 50 Winner, 2024), we are at the forefront of esports analytics and gaming innovation, laying the foundation for a new era in entertainment.    Our technology empowers industry giants like ESPNbet, Betano, Stake, Betway, OpenBet, and Softswiss, setting new standards in the space.  Backed by top investors from North America, the UK, and Singapore, we are profitable, ambitious, and rapidly expanding.   🚀 Join us. Together, we will define the future.   You'll be on a team with people who have quantitative and mathematical backgrounds. Our main focus is building mathematical models for traditional sports. This involves an iterative model-building approach, putting those models into practice, validating and testing them thoroughly, analyzing and processing lots of data, and collaborating with other teams in the company. We primarily code in Python. Being proactive is really valued here, and we offer plenty of freedom for you to bring your great ideas forward.   What You'll Be Working On:   👍 Analyzing patterns and strategies across a wide range of sports, mainly in traditional sports, to uncover key insights. 👍 Designing, implementing, and validating mathematical models to simulate potential game scenarios and outcomes, with a focus on probabilities. 👍 Creating innovative models that integrate real-world factors, such as player psychology, to enhance predictive accuracy. 👍 A stimulating and creative role that involves applying a diverse set of mathematical skills, from writing optimized code to exploring advanced mathematical concepts.   Skills You’ll Need:   ✔ Proficiency in Python programming and git, with a strong focus on practical application. ✔ Solid foundation in university-level linear algebra and calculus - a must for building complex models and solving problems. ✔ A good understanding of probability theory; or knowledge of measure theory and strong willingness to learn. ✔ Hands-on experience in modeling real-world phenomena using mathematical methods.