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MDPI is scaling a portfolio of data-centric and AI-enabled products that enhance editorial quality, spanning publication ethics, expertise matching, copyediting, and typesetting, while also driving operational efficiency through the automation of routine workflows. Building on this foundation, we are expanding AI integration across the full publishing ecosystem to improve the experience of authors, reviewers, editors, and readers alike. To support this growth, we are seeking a Product Owner who can translate strategic direction into high-impact delivery across our AI product initiatives. In this role, you will own delivery outcomes for a portfolio of AI-driven solutions that strengthen core publishing workflows while enabling new user-facing capabilities and future business models. Working closely with AI engineering, data engineering, and platform teams, you will partner with Product Management, Product Design, and key business stakeholders to define value, shape and prioritize the backlog, validate product increments, and continuously iterate toward measurable outcomes, fully aligned with MDPI’s business and technology strategy. As part of our commitment to fostering a collaborative team environment, this role requires working fully on-site.
Job Responsibility:
Translate MDPI business and technology strategy into clear product outcomes and value hypotheses
Help to identify and conceptualize new AI-based offerings and related research (including qualitative methods, such as user interviews)
Champion data-driven decisions and insights generation
stakeholder management and communication
Support North Star definition and ensure the product roadmap reflects incremental or new value generation, while reducing risks
Maintain product goals, KPIs, and benefit / value tracking for data-centric and AI products
Support market, competitor, and user research to inform opportunity sizing and prioritization
Define personas, user journeys, and data-driven problem statements
validate with experiments and prototypes
Ensure AI use cases follow “AI assists, humans decide” principle and are ethical, transparent, auditable, and fair
Own and continuously refine the product backlog (epics, features, stories) with user stories and clear acceptance criteria
Prioritize for impact, feasibility, and dependency alignment across AI/data/platform teams
Plan and run Agile ceremonies
coordinate cross-team delivery and manage release readiness
Define success metrics
ensure metrics are effectively tracked and followed-up
evaluation datasets
and human-in-the-loop quality gates
Address data governance, privacy, security, and model risk considerations with engineering and compliance
Drive post-release validation, incident follow-up, and continuous improvement
Partner with business/operations on enablement, documentation, training, and rollout plans
Partner with product growth managers and product marketing on business model finding, pricing and pricing experiments, measure adoption, engagement, and ROI
Requirements:
Master’s degree in Product Management, Computer Science, Business Management, Information Systems, or a related field
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