About the job
At Oddin.gg, we are not just trend followers; we are trendsetters. Recognized as the fastest-growing tech company in Central Europe (Deloitte Fast 50 Winner, 2024), we lead the charge in esports analytics and gaming innovation, paving the way for a new era in entertainment.
Our cutting-edge technology supports industry leaders like ESPNbet, Betano, Stake, Betway, OpenBet, and Softswiss, establishing new benchmarks in the field. With backing from top-tier investors across North America, the UK, and Singapore, we are not only profitable but also ambitious and rapidly growing.
Join us as we shape the future together.
You will collaborate with a team of professionals with quantitative and mathematical expertise. Our primary mission involves constructing mathematical models for traditional sports. This role demands an iterative model-building process, implementing those models in practice, validating and rigorously testing them, analyzing extensive data sets, and working closely with various teams within the company. Our preferred programming language is Python, and we highly value proactive individuals who are eager to share their innovative ideas.
Key Responsibilities:
Analyze patterns and strategies across a diverse range of traditional sports to uncover significant insights.
Design, implement, and validate mathematical models to simulate potential game outcomes and scenarios, emphasizing probabilities.
Create innovative models that consider real-world factors, including player psychology, to improve predictive accuracy.
Engage in a stimulating and creative role that applies a broad spectrum of mathematical skills, from writing optimized code to exploring complex mathematical concepts.
Required Qualifications:
Strong proficiency in Python programming and git, with a focus on practical applications.
Solid foundation in university-level linear algebra and calculus, essential for complex model construction and problem-solving.
Good understanding of probability theory; knowledge of measure theory is a plus with a willingness to learn.
Hands-on experience in modeling real-world phenomena using mathematical techniques.
