Technical Product Owner – Data & AI

About the role

We are looking for a Technical Product Owner with deep expertise in Data & AI to lead the creation of data‑driven products and AI solutions. The role bridges business stakeholders and engineering teams, ensuring that data initiatives align with strategic goals and deliver measurable impact.

Key responsibilities

• Act as the Product Owner for Data & AI initiatives, managing the product backlog, prioritizing features, and defining user stories.
• Collaborate closely with Data Engineers, Data Scientists, and AI teams to translate business requirements into technical solutions.
• Drive the end‑to‑end lifecycle of AI/ML and data products, from ideation and requirements gathering to deployment and monitoring.
• Ensure alignment of data strategies with business objectives, including analytics, predictive modeling, and AI use cases.
• Define technical product roadmaps and promote best practices in data architecture, governance, and AI deployment.
• Work with stakeholders to understand needs and turn them into actionable features.
• Measure product performance using relevant KPIs and iterate on features for continuous improvement.
• Stay abreast of the latest trends in AI, machine learning, and data technologies, evaluating opportunities for innovation.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Engineering, or a related field.
• Proven experience as a Technical Product Owner in data‑intensive or AI‑focused projects.
• Strong understanding of data engineering, AI/ML models, data pipelines, and cloud data platforms (AWS, Azure, GCP).
• Experience with analytics and AI/ML frameworks such as TensorFlow, PyTorch, and scikit‑learn, as well as data visualization tools.
• Solid knowledge of agile methodologies, backlog management, and working with cross‑functional teams.
• Excellent communication skills to bridge technical and business conversations.
• Strong problem‑solving abilities and a data‑driven approach to product decisions.

Required skills

• AWS
• Azure
• GCP
• TensorFlow
• PyTorch
• scikit-learn
• Data engineering
• AI/ML models
• Data pipelines
• Data visualization tools
• Agile methodologies