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Senior Data Product Manager - Experimentation

Super - Spain

Posted Jun 12, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Market context

Median wage (BLS OEWS)
$111,944 national median
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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About this role

Senior Data Product Manager - Experimentation Spain We are on a mission to pioneer the world's next era of play. As we grow across Europe and Latin America, we're building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day. As Senior Data Product Manager - Experimentation , you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining what we build and why - ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at Super to rapidly experiment, reduce time-to-insight, and drive measurable business impact. What the role involves Product strategy & vision Develop a clear, long-term product vision for the Experimentation Platform, aligning with broader data-driven objectives. Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge. Defining the "what" and "why" Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics. Advocate for hypothesis-driven development, evangelising experimentation methodologies across

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