Quantitative Sports Trader Intern
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Job Description
About Ivy Pointe Capital
Ivy Pointe Capital is a research-driven sports trading firm applying hedge fund principles to global betting markets. They use quantitative modeling, statistical arbitrage, and data-driven forecasting to identify and capitalize on inefficiencies in sports markets. Their core focus spans MLB, NBA, NFL, and NCAA sports, but they are open to other sports based on interest and expertise.
Internship Overview
Ivy Pointe Capital is seeking a driven, analytically-minded Quantitative Sports Trader Intern to support their modeling and pre-match trading operations. This internship is ideal for students or recent grads in statistics, finance, data science, business analytics or related fields who are passionate about sports and quantitative markets.
Key details:
• Location: Remote (U.S. preferred)
• Type: Internship (Part-time or Full-time)
• Duration: 8–12 weeks (flexible)
• Start Date: Rolling
• Compensation: Academic internship credits only (unpaid role; opportunity for bonuses based on model performance)
What You’ll Do:
• Build, test, and refine predictive sports betting models
• Analyze historical and real-time data to identify profitable edges
• Assist in daily pregame simulations and pricing analysis
• Track model performance and improve back testing infrastructure
• Collaborate on trade execution and risk management strategies
• Contribute to internal research presentations and insights
What We’re Looking For:
• Pursuing or completed a degree in Statistics, Finance, Economics, Data Science, Math, Business Analytics or Computer Science
• Proficiency in Python, R, or similar languages
• Proficiency in Excel
• Familiarity with betting markets, sports statistics, or trading strategies
• Strong analytical thinking and attention to detail
• Experience with data visualization or dashboard tools is a plus
• Bonus: Experience with scraping, API usage, or time series modeling
What You’ll Gain:
• Mentorship from a growing team of quantitative sports traders
• Real-world experience in model-driven betting and risk management
• Hands-on exposure to performance tracking, edge validation, and fund management
• Opportunity to convert to a full-time role or long-term contributor
