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Fanatics is a leading global digital sports platform serving over 100 million sports fans worldwide. The company operates across three main pillars: Fanatics Commerce (licensed fan gear and merchandise), Fanatics Collectibles (physical and digital trading cards and memorabilia), and Fanatics Betting & Gaming (sportsbook and iGaming platform). With partnerships spanning 900+ sports properties, 2,500 athletes and celebrities, and 2,000+ retail locations, Fanatics is reshaping how fans engage with sports.
As a Quantitative Analyst I, you will operate at the intersection of sports trading, mathematics, and data science. Your primary focus will be analyzing sports and betting data, developing predictive models, and assisting with trading decisions that drive the company's proprietary trading platform.
Key responsibilities include:
- Model Development: Assist in developing, implementing, training, and testing mathematical models for pricing and managing risk of sports betting events.
- Data Sourcing & Analysis: Collect and clean sports-related data; analyze large datasets of play-by-play (simulated or historical) and betting data to identify patterns, trends, and correlations that inform trading strategies.
- Programming: Use C# or Python to develop quantitative models, code and automate analytical processes, and perform data analysis tasks.
- Collaboration: Work with senior quantitative analysts, traders, and product managers to understand business requirements, implement solutions, and communicate findings effectively. Document models, methodologies, and analysis procedures.
- Continuous Learning: Stay current with developments in quantitative analysis, betting markets, and related fields through self-study and training.
You'll collaborate closely with senior quants, traders, engineers, and product managers to continuously improve pricing efficiency, expand the range of betting odds, and enhance risk models and management strategy. This is a hybrid role requiring 2-5 days per week in the Dublin office, offering an exciting opportunity for professional development in a dynamic, fast-paced environment.
Required qualifications include a Bachelor's or Master's degree in Mathematics, Statistics, Computer Science, Finance, Economics, or a related quantitative field; outstanding mathematical, statistical, and analytical skills; excellent work ethic and team skills; and a detail-oriented mindset committed to high-quality work and best practices in quantitative analysis.
