Data Product Owner

Description

We are seeking a Data Product Owner to lead the vision, strategy, and execution of our data and AI/ML products. This role bridges business stakeholders, data engineering, and data science, ensuring that our data assets, analytics platforms, and machine learning models deliver measurable value. The ideal candidate combines product management expertise with strong knowledge of data, analytics, and applied AI/ML.

Responsibilities

• Define and own the roadmap for data and AI/ML products (data platforms, APIs, dashboards, predictive models, recommendation engines, NLP/vision solutions, etc.)
• Translate business goals into AI/ML-enabled product strategies that drive automation, insights, and competitive advantage
• Partner with business stakeholders to identify opportunities where AI/ML and advanced analytics can create value
• Act as the key interface between data scientists, engineers, and business units, aligning priorities across teams

• Maintain and refine product backlog; write detailed user stories with business and technical acceptance criteria
• Work closely with data scientists to design, build, and deploy ML models into production
• Ensure data quality, explainability, scalability, and performance are built into all products
• Oversee the lifecycle of ML models (development, deployment, monitoring, retraining)

• Ensure data and AI/ML products comply with internal policies and regulatory requirements (GDPR, responsible AI, gaming/financial regulations)
• Have minimal knowledge in MLOps, metadata management, and data governance

Requirements

• Proven experience as a Product Owner / Product Manager in data, AI/ML, or analytics-focused products
• Strong understanding of data science workflows, machine learning lifecycle
• Domain knowledge in iGaming, fintech, or other data-intensive industries
• Understanding of responsible AI, model explainability, and bias mitigation
• Ability to identify and prioritize high-value AI/ML use cases
• Familiarity with data engineering and BI platforms
• Hands-on exposure to AI/ML concepts (predictive modeling, NLP, computer vision, recommendation systems)
• Excellent communication and stakeholder management skills, with the ability to align technical and business teams
• Experience with Agile/Scrum and product backlog management