Manager, Product Analytics and Experimentation

Live Nation Worldwide, Inc. (Ticketmaster) is hiring a Manager, Product Analytics and Experimentation to build and scale a product experimentation practice. The role leads experiment design and execution, analyzes results, and turns findings into recommendations that inform product strategy and improve the fan experience.

Responsibilities:

• Lead and scale the product experimentation program, including processes, governance, measurement standards, and team onboarding
• Serve as the hands-on subject-matter expert for Optimizely, including experiment setup, audience targeting, QA, instrumentation validation, and test monitoring
• Partner with cross-functional teams to identify testing opportunities and design statistically sound A/B, multivariate, and other experiments
• Interpret experiment results, explain what they mean and where they fall short, and turn findings into recommendations that shape product strategy and roadmap decisions
• Work with stakeholders to define and measure key digital metrics tied to fan and business goals
• Use data analysis to find trends, patterns, and opportunities that improve the end-to-end fan experience
• Build analytics tools, methods, and self-service resources that help teams make better data-informed decisions
• Translate business questions into analytical and experimentation solutions
• Build strong relationships with stakeholders and counterparts across the North America Insights and Analytics organization
• Partner with the Research team to combine behavioral, experimental, and qualitative insights into a deeper understanding of fan needs

Requirements:

• Demonstrated experience leading and executing a product experimentation program, from hypothesis development and test design through implementation, analysis, and recommendations
• Hands-on experience with Optimizely or a comparable experimentation platform, including configuring, QA-ing, launching, and monitoring experiments
• Advanced statistical knowledge, including hypothesis testing, power analysis and sample-size planning, confidence intervals, sequential testing, multiple-comparison correction, and variance reduction techniques
• Proven ability to spot and address common experimentation pitfalls, such as sample ratio mismatch, peeking, novelty effects, and interaction effects between concurrent tests
• Ability to design and run complex product experiments, including A/B and multivariate tests
• Advanced proficiency with AI tools and LLMs to speed up and scale analytics work, such as writing and debugging queries, automating recurring analysis and reporting, generating test hypotheses, and summarizing results
• Strong judgment to check AI output for accuracy
• Experience with digital analytics tools such as Google Analytics and Contentsquare
• Advanced SQL proficiency, with hands-on experience in Databricks and Google BigQuery
• Excellent communication and presentation skills, with the ability to turn complex analytical and experimental findings into clear, compelling stories for non-technical audiences
• Partners with stakeholders to understand their needs, build analytical frameworks, and deliver data-driven strategic insights
• Coaches and enables others, helping teams build confidence and skill in experimentation
• Builds rapport and trust with diverse team members
• Brings curiosity and intellectual honesty, and is willing to let the data challenge assumptions, including their own
• Is open to diverse perspectives and ideas
• Focuses on the highest-impact work
• Manages time well to meet deadlines and commitments
• Adapts to changing priorities and environments
• Stays resilient through setbacks and obstacles