Data & Platform Manager

IUCN, in collaboration with the University of Melbourne and several Red List of Ecosystems partners, is rebuilding the Red List of Ecosystems (RLE) data platform. The new system will support the storage, management, and dissemination of RLE data, enable the timely delivery of new assessments, and improve the use of results for decision-making.

The development phase will focus on:

• Streamlining workflows for data ingestion, storage, validation, and publication.
• Enhancing the user experience to improve access to existing assessments and accelerate the production of new ones.
• Integrating AI and machine-learning methods, where appropriate, to support analysis and assessment processes.
• Ensuring interoperability with related systems, including other IUCN data products such as the Red List of Threatened Species and relevant external systems.

The Data & Platform Manager - Red List of Ecosystems, will play a central role in shaping the overall vision for the Red List of Ecosystems (RLE) data platform. This new system will support the storage, management, and dissemination of RLE data, enable the timely delivery of new assessments, and improve the use of results for decision-making. The position will be key in coordinating with partners and stakeholders and driving the delivery of the IUCN RLE platform. The purpose of this position is to lead product strategy, planning, and execution for the Red List of Ecosystems digital platform, encompassing both web development and data management. The role ensures that the platform meets user needs, aligns with IUCN's strategic priorities, and adheres to responsible AI practices and robust data governance standards. The Data & Platform Manager - Red List of Ecosystems will also work closely with the IUCN Conservation Informatics team (including the Red List Data Manager and the Red List Systems Manager), the IUCN Program Manager for the Red List of Ecosystems, and a range of external collaborators from partner institutions to achieve these goals., The Data & Platform Manager - Red List of Ecosystems will be responsible for the development, maintenance, and long-term sustainability of the Red List of Ecosystems (RLE) database and associated digital platforms. The role combines IT product management and data management functions, working closely with scientific teams, IT partners, and external data providers.

1.Product Strategy & Roadmapping

• Develop, maintain and update a long-term product roadmap for the Red List of Ecosystem's digital platform, data infrastructure, and AI-assisted tools, ensuring sustainability beyond immediate project cycles.
• Define and articulate product vision, success metrics, and phased delivery plans for platform development, maintenance, and evolution.
• Facilitate workshops with stakeholders and partners to align priorities.
• Prioritise features and technical enhancements using measurable criteria (impact, feasibility, risk, scalability, data maturity, AI readiness).
• Ensure alignment with IUCN's digital transformation policies, the Conservation Data Hub vision, and interoperability between Red List of Ecosystems and other IUCN data products like the Red List of Threatened Species
• Contribute to planning for long-term platform resourcing, technical debt management, and lifecycle management of software and data assets.

2. Requirements Gathering & User Experience

• Manage external consultant work/service provision, on user research, system design or technical development ensuring to translate outputs into formal requirements and user stories.
• Map end-to-end data flows: ingestion, validation, versioning, assessment, review and publication.
• Ensure user-centred design principles are applied, with strong attention to accessibility, usability, multilingual support, and varying technical capacities of global users.
• Maintain up-to-date system and data flow documentation to support onboarding, knowledge transfer, and long-term maintainability.

3 AI & Data Functionality

• Identify, assess and prioritize use cases where AI/ML can support RLE processes (e.g., automated data checks, geospatial anomaly detection, ecological similarity modelling, NLP support for documentation).

• Collaborate with scientists and developers to design safe and transparent AI features.

• Define evaluation metrics and quality assurance processes for AI supported functions.

• Support the design and development of data pipelines, , metadata standards, and data models

• Contribute to development of embedding, Model Context Protocols (MCP), Retrieval Augmented Generation (RAG) and any other AI standards and techniques where appropriate.

4 Project Coordination & Delivery

• Coordinate with partners the product backlog, sprint planning, and release schedules.
• Coordinate activities across software developers, DevOps, data engineers, and scientific contributors.
• Oversee integration with existing IUCN systems.
• Monitor delivery progress, dependencies, and risks, and proactively address delays or resource constraints.

5 Data Management, Governance, Risks & Compliance

• Act as data steward for the RLE database, ensuring high standards of data quality, consistency, completeness, and documentation.
• Establish and maintain data governance processes, including data standards, validation rules, version control, audit trails, and long-term archiving strategies.
• Ensure appropriate data sharing agreements, licences, and permissions are in place with partners and contributors, in line with IUCN policies and international best practice.
• Define a data governance framework with the definition of accountability and standard processes for monitoring data quality.
• Establish data security policies with different degrees of protection according to different categories and with role definition that defines access
• Champion data integrity creating procedures to protect the Red List of Ecosystems data from data loss and inaccuracies.
• Set up a data and disaster recovery plan.
• Ensure compliance with IUCN data policies, responsible AI guidelines, and privacy/ethics principles.
• Identify and mitigate risks related to data quality, cybersecurity, AI bias, and system reliability.
• Maintain documentation of data models, APIs, standards, and governance decisions.

6 Stakeholder Engagement

• Coordinate consultations, feedback sessions, and user-testing cycles to continuously improve platform functionality and data workflows.

• Communicate product decisions and rationales clearly to both technical and non-technical audiences.

• Support capacity building by contributing to guidance materials, training resources, and best-practice documentation for data contributors and users. REQUIREMENTS

• Essential

Undergraduate degree or equivalent work experience in computer science, information systems, environmental science or a related field. -Demonstrated minimum of 8 years of professional experience in product management, technical coordination, or data management for digital platforms, particularly data-intensive or analytics-enabled systems. Experience of minimum 2 years within a multinational environment -Solid working knowledge of data management and governance practices, including data quality control, validation workflows, documentation, versioning, and data sharing arrangements. -Experience contributing to or supporting AI- or automation-enabled functionalities -Ability to translate scientific or domain-expert requirements into clear technical requirements, user stories, or system specifications. -Experience working with multidisciplinary teams (e.g. developers, data engineers, scientists, UX or data specialists) and coordinating contributions from internal and external partners. -Strong communication, organisational, and prioritisation skills, with the ability to work effectively with both technical and non-technical stakeholders in an international context. -Experience working in an Agile environment. -Fluency in one IUCN official language and local language.

*Desirable -Experience with conservation, biodiversity, ecosystem, or environmental data systems. -Familiarity with geospatial data and GIS concepts, including spatial databases or APIs. -Working knowledge of cloud-hosted platforms and modern data infrastructures. -Exposure to large language models (LLMs), AI-assisted data workflows, or advanced data integration approaches (e.g. RAG, vector databases). -Familiarity with the IUCN Red List of Ecosystems and/or Red List of Threatened Species processes. -Experience working in an international, non-profit, or mission-driven organisation. APPLICATIONS

IUCN is a membership Union uniquely composed of both government and civil society organisations. It provides public, private and non-governmental organisations with the knowledge and tools that enable human progress, economic development and nature conservation to take place together. Created in 1948, IUCN is now the world's largest and most diverse environmental network, harnessing the knowledge, resources and reach of more than 1,400 Member organisations and around 16,000 experts. It is a leading provider of conservation data, assessments and analysis. Its broad membership enables IUCN to fill the role of incubator and trusted repository of best practices, tools and international standards. IUCN provides a neutral space in which diverse stakeholders including governments, NGOs, scientists, businesses, local communities, indigenous peoples organisations and others can work together to forge and implement solutions to environmental challenges and achieve sustainable development. Working with many partners and supporters, IUCN implements a large and diverse portfolio of conservation projects worldwide. Combining the latest science with the traditional knowledge of local communities, these projects work to reverse habitat loss, restore ecosystems and improve people's well-being.