Senior Data Product Manager - Experimentation

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. Overview As a 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 SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key Responsibilities

1. Product strategy vision Develop a clear, long-term product vision for the Experimentation Platform , aligning with the broader data-driven objectives. Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2.

Requirements

into well-defined problem statements, expected business impact, and success metrics. Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization. 3.

Roadmap stakeholder management Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.

, and drive alignment. 4. Cross-functional collaboration Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.

Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks. Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys. 5.

, user stories, and acceptance criteria to engineering teams. Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress. Ensure each initiative launches with a defined Problem to Solve , Business Impact , and Success Measurement , tracking progress to inform continuous improvement.

6. ) and implement tracking mechanisms. Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.

Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.

, and iterate on platform improvements. 7. Domain expertise thought leadership Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.

Lead initiatives like an Experimentation Embassy , workshops, and knowledge-sharing sessions to promote best practices across the company. 8. Communication evangelism Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.