Quantitative Sports Researcher | Experienced Hire

Susquehanna International Group · Dublin

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At Susquehanna, the Sports Analytics team builds statistical forecasting models that help provide liquidity for the sports betting industry. These models are vital to creating new trading strategies and informing decision-makers about the distribution of game events. By joining our Sports Analytics team, you will be part of a group that is passionate about mathematics, gaming, and technology.

In this role, you will: 

• Immerse yourself in sports analytics and quantitative trading research
• Empirically test ideas using real industry data
• Write programs to implement models, and strategies  
• Collaborate with fellow researchers, traders, and technologists
• Spend time trading to understand how models are used in practice and how traders think and operate, ensuring model development is grounded in real-world insight
• Occasionally provide off-hour coverage, which may include evening or weekend shifts, while developing this understanding and when deploying or testing new models / strategies

• Strong quantitative and analytical skills, with a background in Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or Economics (advanced degree a strong plus but not required)
• Excellent logical reasoning and problem-solving skills
• Exceptional communication skills, with the ability to both understand others and clearly express your ideas
• Experience writing code to process and analyze large sets of data
• Demonstrated experience working on sports analytics projects or other quantitative projects
• Familiarity with sports such as NFL, NBA, MLB, NHL, NCAAF, NCAAM, soccer, tennis, or golf, as well as trading experience, is a plus but not required
• Intermittent international travel may be required

If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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