Data Scientist

Data Scientist

Fanatics is building a leading global digital sports platform. The company ignites the passions of global sports fans and maximizes the presence and reach for hundreds of sports partners globally by offering innovative products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans, a global partner network with over 900 sports properties, including major national and international professional sports leagues, teams, players associations, athletes, celebrities, colleges, and college conferences, and over 2,000 retail locations, including its Lids retail business stores.

As a market leader with more than 20,000 employees, and hundreds of partners, suppliers, and vendors worldwide, we take responsibility for driving toward more ethical and sustainable practices. We are committed to building an inclusive Fanatics community, reflecting and representing society at every level of the business, including our employees, vendors, partners and fans. Fanatics is also dedicated to making a positive impact in the communities where we all live, work, and play through strategic philanthropic initiatives.

For information about our benefits, please visit https://benefitsatfanatics.com/

We are seeking a Data Scientist III to join our growing Data Science organization on our newly formed Decision Science team. The role reports into the Decision Science Manager and will focus on creating insight to drive the growth of the business, partnering closely with senior commercial stakeholders and their teams.

Supporting commercial and analytics stakeholders with high level Sportsbook & Casino strategy will be a top priority for this Data Scientist, as well as providing ongoing analysis and recommendations to stakeholders.

Responsibilities

• Develop a deep understanding of the iGaming ecosystem, encompassing both Sportsbook and Casino products, operations, and player behavior.
• Build strong relationships with stakeholders across both Sports and Casino business units, serving as a key technical contributor to driving total commercial performance.
• Collaborate with Data Scientists and Analysts to implement and refine scalable solutions for complex iGaming business problems.
• Contribute to the development, deployment, and iterative improvement of automated personalization and promotion engines across the iGaming suite.
• Build and maintain sophisticated Lifetime Value (LTV) models to improve player segmentation and marketing efficiency.
• Remain current on technology, machine learning trends, and competitive shifts within the global sports betting and gaming industry.

Experience and Skills

• A minimum of 3-5 years proven experience in a data science or advanced analytics role.
• Degree in a quantitative field, e.g., Mathematics, Physics, Statistics, Engineering, or Computer Science, Economics.
• Strong SQL proficiency and strong proficiency in Python, with experience building and validating machine learning models.
• Strong understanding of statistics concepts such as regression, clustering, and A/B testing in high-growth environments.
• Expertise in experimental design and causal inference, including A/B/n testing, quasi-experiments, and uplift modeling to determine true incremental value.
• Demonstrated ability to partner with stakeholders, earning trust through data-driven insights and clear communication.
• Outcome-oriented and data-driven; comfortable navigating fast-paced, high-growth environments.

Preferred but not required

• Experience experimenting with Generative AI solutions (e.g., LLM-based analysis, automation, or insight generation) and identifying opportunities to apply them within a commercial analytics environment.
• Previous experience in iGaming (Sportsbook or Casino), or previous experience with Customer Lifetime Value models is a significant plus.