We’re defining what it means to build and deliver the most extraordinary sports and entertainment experiences. Our global team is trailblazing new markets, developing cutting-edge products, and shaping the future of responsible gaming.

Here, “impossible” isn’t part of our vocabulary. You’ll face some of the toughest but most rewarding challenges of your career. They’re worth it. Channeling your inner grit will accelerate your growth, help us win as a team, and create unforgettable moments for our customers.

The Crown Is Yours

We’re seeking an Analyst to monitor, measure, and enhance the health and performance of our Partnerships Marketing initiatives. By fostering cross-functional collaboration and innovating in metric development, you’ll enable teams throughout our organization to make more informed, improved and expedited decisions.

What you’ll do as an Analyst, Marketing Analytics

• Work with a team of marketing analysts responsible for monitoring business and customer performance for our marketing channels, such as television, radio and influencers. Example areas include  measuring the performance of marketing campaigns using statistical methods accounting for state, sports and competitive trends.

• Work closely with our Partnerships teams to identify areas of opportunity, align on key performance indicators, measure performance and provide data driven recommendations.

• Build and maintain a reporting suite to support critical initiatives.

• Create high-quality presentations to communicate with key stakeholders across the business effectively.

• Design and execute against a testing agenda to advance our overall marketing strategy.

• Work cross-functionally across operations, promotions, product, and VIP to understand customer behavior.

What you’ll bring

• 2+ years of business analytics or data science experience at a B2C company.

• Bachelor’s degree or equivalent in Mathematics, Statistics, Economics, Computer Science, Engineering, Business Analytics, or another relevant discipline.

• Experience with SQL and Python, R, or other statistical programming languages.

• Comfortable in a fast-paced, results-driven environment.

• Strong knowledge of statistics and hypothesis testing.