quantitative analysis team lead engineer.

As a Quantitative Analysis Team Lead Engineeryou will :  

• Develop quantitative models and tools to optimize trading across various sports, focusing on optimal techniques and technologies for continuous improvement of price accuracy, performance and content
• Lead the development and maintenance of models, taking ownership of new features from conception to delivery
• Build pre-match and in-play derivative pricing models on a wide variety of sports
• Create predictive models spanning diverse sports
• Maintain and enhance all models through ongoing model validation and improvements
• Design clear and efficient workflows, development environments, data capture tools and continuous education and improvement programs
• Lead and inspire a team of quantitative analysts, fostering a collaborative and high-performance work environment
• Mentor and train team members, promoting skill development and career growth
• Manage project timelines, priorities, and resources to ensure the timely delivery of analytical solutions
• Provide technical guidance, expertise, and code reviews to ensure the quality and adherence to best practices of analytical models
• Contribute to architectural decisions and design of analytical systems, considering scalability, performance, and maintainability

2+ years of experience in similar role 

• 3 years + of experience in a quantitative role, ideally within the sports betting industry.Strong analytical thinking skills and expertise in probabilistic and statistical modeling
• Proficiency in statistical languages such as Python or R.Experience with simulation and optimization techniques.Leadership and project management experience, with the ability to guide and motivate a team
• Excellent communication skills for effectively collaborating within a team and presenting findings to stakeholders.A solid understanding of the gaming industry and an interest in sports will be considered as a plus
• Bachelor's degree in Mathematics, Statistics, or a related scientific discipline
• Κnowledge of programming languages for model implementation (object-oriented principles, data structures, functional programming principles, knowledge in C#) will be considered as a plus