Senior Data Product Manager - Experimentation

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.

• 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.
• Translate business goals and user 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.
• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.
• 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.
• Clearly communicate product requirements, 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.
• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) 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.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.
• 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.
• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.
• Strong familiarity with A/B testing , multivariate testing , feature flag management , and audience segmentation .
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.
• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.
• Hands-on experience building experimentation platforms , customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.