Quantitative Sports Researcher | Experienced Hire

Overview

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
  
  

What We're Looking For

• 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 [email protected]. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.