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Salary: USD 161,500 - 212,500 / annual
Fanatics is a global digital sports platform serving over 100 million sports fans through commerce, collectibles, and betting/gaming. Fanatics Betting and Gaming, launched in 2021, operates the Fanatics Sportsbook (available to 95% of the US addressable online sports betting market) and Fanatics Casino across multiple states, with retail locations including the only sportsbook inside an NFL stadium.
You will own product strategy for customer-facing machine learning applications within the flagship product, directly tied to key ecosystem objectives: customer acquisition cost, cross-sell rates, and engagement. This is a high-visibility role at the center of how Fanatics measures and improves the impact of growth investments.
Key responsibilities include:
- Own product strategy for customer-facing ML applications, aligned with ecosystem group KPIs (CAC, cross-sell, engagement)
- Design non-deterministic product solutions where ML models play a central role; determine where ML adds genuine value
- Define how model performance is measured and evaluated, including measurement frameworks for probabilistic outputs
- Run experimentation and testing as a core decision-making process for shipping features
- Partner with ML engineers and data scientists on requirements and evaluation; collaborate with commercial and CRM teams pursuing revenue targets
- Translate between technical and non-technical stakeholders, educating partners without ML or quantitative backgrounds
- Make pragmatic tradeoffs and move quickly, balancing model quality against business needs
You will work closely with engineers, data scientists, and product and commercial partners to bring ML into the customer experience and drive growth across the Fanatics ecosystem.
Requirements:
- Senior product management experience with a track record in product growth, experimentation, or data-driven consumer products
- Quantitative background: statistics, measurement for probabilistic systems, or experience with LLM evaluation frameworks
- Ability to make ML-specific product decisions and evaluate model performance (prior data science experience not required)
- Experience in consumer-facing product environments with large user bases and mature data and experimentation practices
- Strong communication skills with patience for teaching non-technical stakeholders
- Flexible, pragmatic mindset: comfortable compromising and moving fast rather than waiting for perfection
