Data and Platform Manager – Red List of Ecosystems

About the role

The Data & Platform Manager for the Red List of Ecosystems will lead the development, maintenance, and long‑term sustainability of the RLE database and its digital platforms. Working closely with scientific teams, IT partners and external data providers, you will combine product management and data stewardship to support IUCN’s conservation data initiatives.

Key responsibilities

• Define and maintain a product roadmap, success metrics and phased delivery plans for the digital platform, data infrastructure and AI‑assisted tools.
• Gather requirements, conduct user research and translate outputs into formal user stories and system specifications.
• Identify, design and evaluate AI/ML use cases such as automated data checks, geospatial anomaly detection and NLP support.
• Coordinate sprint planning, backlog management and release schedules across developers, DevOps, data engineers and scientific contributors.
• Act as data steward, establishing governance processes, validation rules, version control, audit trails and disaster‑recovery plans.
• Engage stakeholders through consultations, feedback sessions and user‑testing cycles to continuously improve platform functionality.

Required profile

• Undergraduate degree or equivalent experience in computer science, information systems, environmental science or related field.
• Minimum 8 years of product management, technical coordination or data‑intensive platform experience, including at least 2 years in a multinational environment.
• Strong knowledge of data management and governance practices, AI/automation integration and Agile methodologies.
• Proven ability to translate scientific requirements into technical specifications and to work with multidisciplinary teams.
• Fluency in one IUCN official language and the local language.

Required skills

• Data governance and quality control
• Data validation and versioning workflows
• Data pipelines and metadata standards
• API design and integration
• Geospatial data handling, GIS concepts and spatial databases
• Cloud‑hosted platforms and modern data infrastructures
• AI/ML integration, Retrieval Augmented Generation (RAG) and Large Language Models (LLMs)
• Agile product development and roadmap planning