Lead the design, development, and implementation of machine learning models to improve various aspects of online poker gameplay, including player behavior analysis, game fairness, fraud detection, and game optimization.
Collaborate with cross-functional teams including product managers, software engineers, and data scientists to define project requirements and deliver high-quality solutions.
Conduct research and stay up-to-date with the latest advancements in machine learning and artificial intelligence techniques applicable to the online poker industry.
Perform thorough data analysis and experimentation to evaluate the performance of machine learning models and identify areas for improvement.
Work closely with software engineers to integrate machine learning models into production systems and ensure scalability, reliability, and efficiency.
Mentor and provide guidance to junior members of the machine learning team, fostering a culture of continuous learning and professional growth.
Requirements & Skills:
Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or a related field.
5+ years of experience in machine learning, data science, or a related field, with a strong emphasis on practical applications.
Proven track record of designing and implementing machine learning models in real-world scenarios, preferably in the gaming or online gambling industry.
Proficiency in programming languages such as Python, Java, or C++, and familiarity with machine learning libraries/frameworks such as TensorFlow, PyTorch, or sci-kit-learn.
Solid understanding of probability theory, statistics, and algorithms, with experience applying them to solve complex problems.
Excellent communication skills and the ability to effectively collaborate with cross-functional teams in a fast-paced environment.
Passion for poker and a deep understanding of the game mechanics, player behavior, and industry trends is a plus.
