Job Description
We’re looking for a Senior Product Optimization Analyst to join a growing Digital Product Optimization team and help drive a culture of experimentation and data-driven decision-making across digital products.
In this role, you’ll partner with Product, Analytics, Design, and Engineering teams to identify opportunities, design rigorous A/B tests, prioritize experiments, and turn results into actionable product decisions.
Responsibilities
Lead and advise teams throughout the experimentation lifecycle, from hypothesis to results.
Define experiment goals, success metrics, test design, sample size, and duration.
Analyze experiment results and translate complex data into clear recommendations.
Help product teams prioritize experiments based on impact, effort, and business value.
Promote experimentation best practices and help teams incorporate testing into their product roadmaps.
Partner with Product Managers, Designers, Engineers, and Data teams across multiple digital products.
Educate and mentor teams to strengthen experimentation and data fluency across the organization.
Requirements
5+ years of experience in A/B testing, experimentation, or product optimization.
Strong knowledge of experimental design, statistical power, and experimentation methodologies.
4+ years of experience with Adobe Analytics or a similar digital analytics platform.
Experience with Adobe Target or another experimentation platform.
Strong ability to turn data from multiple sources into actionable business and product insights.
Excellent communication and stakeholder management skills.
Experience working across Product, Design, Engineering, and Analytics teams.
Ability to influence and drive decisions in a complex, matrixed environment.
Strong organizational skills and ability to manage multiple experiments and initiatives simultaneously.
Preferred Skills
Experience with eCommerce, travel, or digital experience products.
Experience with Jira and Agile product development.
Experience with advanced experimentation scenarios.
Experience mentoring teams or building experimentation programs.
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