Product Manager, Data and Artificial Intelligence

Role overview

What you’ll accomplish

• Define product vision, business objectives, target audiences, and value propositions for data and AI products.
• Build and communicate roadmaps aligned with strategic priorities, expected value, risks, dependencies, and delivery capacity.
• Translate business and user needs into problem statements, value hypotheses, functional requirements, acceptance criteria, and user stories.
• Prioritize the backlog across business value, technical feasibility, data quality, integration complexity, security, compliance, and user experience.
• Lead discovery and validation through proofs of concept, prototypes, pilots, user testing, A/B testing, and phased rollouts.
• Collaborate with data, AI, engineering, architecture, cybersecurity, privacy, compliance, risk, UX, and business teams.
• Define product success metrics for adoption, usage, satisfaction, business value, operational performance, and model performance where appropriate.
• Monitor deployed solutions for benefits, quality, bias, drift, performance, and adoption; prioritize continuous improvement.
• Embed ethics, transparency, explainability, security, privacy, and data governance into products.
• Communicate recommendations, trade-offs, progress, risks, and results to stakeholders and governance committees.
• Contribute market intelligence on generative AI, intelligent agents, RAG, automation, advanced analytics, and data platforms.

What could help you thrive

• Significant experience in product management, technology solution delivery, analytics, data, or AI.
• Ability to translate complex business needs into high-value data and AI products.
• Strong business acumen, prioritization, data-driven decisions, and stakeholder influence.
• Solid understanding of data governance, machine learning, generative AI, large language models, intelligent agents, and responsible AI.
• Awareness of security, privacy, ethics, regulatory compliance, and risk management.
• Experience collaborating with multidisciplinary teams in an Agile or hybrid environment.
• University degree in Business Administration, Computer Science, Software Engineering, Data Science, Analytics, Information Systems, Finance, or another relevant discipline.
• Advanced English proficiency is required for regular collaboration with English-speaking stakeholders, presentations, committees, vendor interactions, and AI initiatives.
• Collaborative leadership, autonomy, rigor, and ability to build alignment around shared objectives.

About the workplace

• The employer describes a collaborative and innovative environment that supports learning and development.