Mathematician

We are seeking an experienced Mathematician to support the development and optimization of mathematical models and algorithmic solutions within our sportsbook platform.

The ideal candidate will bring strong expertise in mathematics, probability, statistics, and algorithmic modeling, combined with a deep understanding of sportsbook mechanics and betting markets. The consultant will work closely with product, trading, and development teams to enhance odds models, improve automation capabilities, and contribute to the development of advanced data-driven solutions.

Key Responsibilities

• Design, review, and optimize mathematical models used in sportsbook trading, odds generation, and risk management.

• Support the development and improvement of algorithmic pricing and automated trading solutions.

• Analyze betting data, market behavior, and performance metrics to improve model accuracy and efficiency.

• Collaborate with Product, Trading, Data Science, and Engineering teams to implement scalable algorithmic solutions.

• Provide expert insights on probability models, margin optimization, and risk exposure management.

• Contribute to the development of data-driven strategies for sportsbook market automation and pricing efficiency.

• Evaluate existing algorithms and identify opportunities for optimization and performance improvement.

• Support the integration of new analytical approaches, including advanced statistical methods and machine learning techniques where relevant.

• Conduct research on industry best practices and emerging technologies in sportsbook modeling and algorithmic trading.

• Provide technical guidance and recommendations on mathematical frameworks used in sportsbook operations.

Requirements

• Strong academic background in Mathematics, Statistics, Data Science, Computer Science, or a related quantitative field.

• Proven experience working with mathematical modeling, statistical analysis, or algorithm development.

• Experience in sportsbook, betting technology, trading systems, or quantitative modeling environments is a strong advantage.

• Deep understanding of probability theory, statistical modeling, and data analysis.

• Experience working with large datasets and performance metrics.

• Familiarity with algorithmic systems, predictive models, or automated decision-making frameworks.

• Strong analytical and problem-solving skills.

• Ability to work closely with technical and product teams to translate mathematical concepts into practical solutions.

• Excellent communication skills with the ability to explain complex quantitative concepts to non-technical stakeholders.

Originally posted on Himalayas