Director, Product Intelligence, AI/ML & Data Solutions

About the Role & Team

ESPN Bet and theScore are leading mobile sports betting and online casino platforms, dedicated to revolutionizing the user experience through data-driven innovation. We are passionate about leveraging cutting-edge technologies to create personalized and engaging experiences. We are seeking a strategic and visionary Director, Product Intelligence, AI/ML & Data Solutions to lead the development and value measurement of next-generation features, powered by data science, advanced analytics and AI, while also providing strategic oversight of the product analytics function. This position will oversee a combination of managers, engineers, data scientists and analysts.  

The Director, Product Intelligence, AI/ML & Data Solutions will be responsible for defining and executing the strategic roadmap for features that leverage data to enhance user engagement and drive business growth. This role combines strategic vision with deep technical understanding to build features that personalize and/or enhance the user experience. You will also oversee the product analytics function, ensuring rigorous measurement and optimization of feature performance through A/B testing, feature discovery, and deep data insights. This leader will be a key collaborator, working closely with engineering, product, strategy, user research, and design teams to discuss ideas, bring innovative features to life and demonstrate their impact. 

About the Work 

• Develop and articulate a strategic roadmap for data-driven feature innovation on topics including personalization, recommender systems, chat toxicity models, AI-powered user experiences, and other advanced applications.
• Identify and evaluate emerging technologies and trends in data science and AI and assess their potential to enhance the user experience.
• Drive the ideation, prototyping, and validation of new feature concepts, ensuring alignment with business objectives and user needs.
• Lead the prioritization and sequencing of solution development, balancing strategic impact with technical feasibility.
• Oversee the development and implementation of data-driven features, ensuring high quality and performance, including working closely with engineering teams to integrate data-driven features into the app.
• Collaborate with engineering teams to ensure that data-driven features are built on a scalable and reliable infrastructure.
• Lead the product analytics function, ensuring rigorous measurement and optimization of feature performance.
• Direct A/B testing initiatives and experimentation protocols to validate assumptions, optimize feature performance, and facilitate iterative enhancements of data-driven products.
• Lead feature discovery work to find gaps and opportunities within the app.
• Collaborate with VP-level stakeholders across engineering, product, strategy, user research, and design to align on product priorities and strategies.
• Communicate effectively with technical and non-technical audiences, translating complex data and concepts into clear and actionable insights.
• Present findings and strategic direction to executive leadership. 

About You 

• 7+ years of proven experience leading teams to deliver data science and analytics solutions at scale in real-world, production-level settings.
• Formal academic background in a technical or quantitative field (e.g., Computer Science, Data Science, Engineering, Statistics); Master's+ degree preferred.
• Proven track record of developing and launching successful data-driven features at scale.
• Strong understanding of machine learning, data science, analytics and AI concepts.
• Experience with product analytics tools and techniques, including A/B testing, data modelling frameworks & visualization best practices.
• Excellent strategic thinking and problem-solving skills.
• Strong communication and presentation skills, with the ability to influence and collaborate with stakeholders at all levels.    
• Passion for innovation and a deep understanding of user experience principles.
• Experience working with engineering and data science teams in an agile environment.
• A balance of technical understanding and creative vision.
• Knowledge of the sports betting industry is preferred, but not mandatory. 

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