Principal Data Product Manager - Machine Learning / AI

Salary

Core Qualifications

Preferred Qualifications

Key Responsibilities

• •Own the long-term product vision and roadmap for ML/AI solutions, in alignment with Superbet’s strategic objectives.
• •Identify and champion high-value ML/AI use cases, balancing quick wins with transformational initiatives that unlock new business potential.
• •Gather and synthesize stakeholder requirements (e.g., from Product, Marketing, Operations) into clear problem statements, business impact, and success metrics.
• •Work with Data Scientists and ML Engineers to ensure solutions are feasible and viable, focusing on outcomes rather than just outputs.
• •Own and maintain a prioritized ML/AI product roadmap, aligning it with company goals, resource availability, and technical constraints.
• •Collaborate with senior leaders and internal stakeholders to manage expectations, refine requirements, and secure support for new initiatives.
• •Partner closely with the Director of ML/AI (and associated engineering teams) to transform product requirements into robust, scalable, and efficient ML pipelines.
• •Coordinate with Data Engineering, Insights, and other Product teams to ensure smooth data flows, model deployment, and feedback loops.
• •Drive alignment on the usage of ML/AI technologies and best practices across the organization.
• •Communicate product requirements, user stories, and acceptance criteria to engineering teams; ensure clarity of priorities and iterative delivery.
• •Champion Agile methodologies (or relevant frameworks) to maintain focus on delivering incremental, high-impact features.
• •Guarantee each project has a well-defined Problem to Solve, Business Impact, and Success Measurement, continuously tracking progress and iterating as needed.
• •Define KPIs and success metrics for ML/AI solutions (e.g., model accuracy, time-to-delivery, user adoption, etc).
• •Analyze performance data to derive actionable insights, optimize outcomes, and refine product roadmap.
• •Communicate progress, challenges, and results to key stakeholders, including executive leadership.
• •Stay current with the latest trends in machine learning, AI research, and MLOps best practices.
• •Advocate for a data-driven culture, evangelizing ML/AI solutions and sharing success stories that highlight their value.
• •Identify opportunities for new or improved AI capabilities that can enhance customer experiences, trust, and satisfaction.
• •Serve as an internal ambassador for ML/AI, presenting product updates, demos, and vision statements to cross-functional teams and executives.
• •Help non-technical stakeholders understand complex AI concepts in plain language, fostering trust, collaboration, and widespread adoption.