Org. Setting and ReportingThe United Nations Environment Programme (UNEP) is the leading global environmental authority that sets the global environmental agenda, promotes the coherent implementation of the environmental dimension of sustainable development within the United Nations system and serves as an authoritative advocate for the global environment. UNEP`s vision for the Digital Transformation of the organization is routed in responding to a changing digital development landscape and the evolving needs of our partners, including government, businesses, finance, and civil society. As such, UNEP continues to seek out and embrace existing and emerging digital technology in all aspects of its work to better serve its partners in their efforts to tackle the triple planetary crises of climate change, nature loss and pollution. Through a process of scanning, testing and scaling relevant digital technologies, UNEP aims to become an increasingly data-driven, agile, transparent and effective partner. UNEP's approach to Digital Transformation is not only about digitalizing our products and services, but also using them to drive transformation changes in five areas: environmental decision-making, economic incentives and business models, human behaviors, and environmental governance. The focus of this job is to use internal and external data for evidence-based decision support by looking at trends, current data and predictions. The Data Scientist will support in accelerating and scaling environmental sustainability through digital transformation, and in the digital transformation of UNEP`s business processes and culture. This position is located in the Chief Digital Office within the United Nations Environment Programme (UNEP) in Nairobi. Under the direct supervision of Chief Digital Officer, the incumbent will be responsible for the following duties: Responsibilities• Heads the Applications, AI and Data Science function, with overall responsibility for UNEP data platforms and applications on both the corporate and programmatic sides. • Plans and directs the work programme on data science, providing both methodical and managerial supervision of all activities; Plans, organizes and manages staff and evaluates their performance. • Takes the lead in exploration, identification, and acquisition of data sources to determine their suitability for use in decision making and advancing the goals of the organization. Enables broader use of data sources by applying quality methods to structure, clean, format, parse, and standardize for analytical use. • Ensures close working relationships with key stakeholders to leverage the use of data science methods to support their programmatic areas with solutions that assist them in accomplishing their mandates. • Coordinates the design and development of data science products to reveal insights and provides an understanding or knowledge of the data that would otherwise not be detected without the application of advanced analytical methods such as artificial intelligence, machine learning, predictive analytics, data and text mining, natural language processing, statistics, and use of relevant algorithms and computational approaches. • Orchestrates the liaison with technology stakeholders to access infrastructure, software and services needed to develop and deploy data science products. • Liaises with the Business Analysis team to translate user requirements into technical roadmaps and supervise their implementation in collaboration with business owners. • Coordinates the design and development of customized visualization and presentation products to reveal the findings of analysis for clients, suitable for all forms of production to include briefings, reports, documentation to oversight bodies, interactive interfaces, and publication quality outputs. • Guides, trains and supervises staff in the function. • Represents the organization and the Chief Digital Officer at international and regional meetings and inter-agency activities, as well as internal meetings as needed. • Advises senior management on trends and developments in data science and recommends appropriate courses of action. CompetenciesPROFESSIONALISM: Knowledge of the software and data analysis life cycles from ingest and wrangling to analysis and visualization to present findings. Excellent analytical and problem-solving skills, ability to build new products and drive new approaches. Ability to convey complex / difficult data science topics to clients in a relatable manner. Takes pride in the work for the organization and understands the impact that can be brought into the organization by allowing data-driven and evidence-based decisions. Ability to apply judgment in the context of assignments given, plan own work and manage conflicting priorities. Shows pride in work and in achievements; demonstrates professional competence and mastery of subject matter; is conscientious and efficient in meeting commitments, observing deadlines and achieving results; is motivated by professional rather than personal concerns; shows persistence when faced with difficult problems or challenges; remains calm in stressful situations. Takes responsibility for incorporating gender perspectives and ensuring the equal participation of women and men in all areas of work. PLANNING & ORGANIZING: Develops clear goals that are consistent with agreed strategies; identifies priority activities and assignments; adjusts priorities as required; allocates appropriate amount of time and resources for completing work; foresees risks and allows for contingencies when planning; monitors and adjusts plans and actions as necessary; uses time efficiently.. MANAGING PERFORMANCE: Delegates the appropriate responsibility, accountability and decision-making authority; makes sure that roles, responsibilities and reporting lines are clear to each staff member; accurately judges the amount of time and resources needed to accomplish a task and matches task to skills; monitors progress against milestones and deadlines; regularly discusses performance and provides feedback and coaching to staff; encourages risk-taking and supports creativity and initiative; actively supports the development and career aspirations of staff; appraises performance fairly.. CLIENT ORIENTATION: Considers all those to whom services are provided to be “clients” and seeks to see things from clients’ point of view; establishes and maintains productive partnerships with clients by gaining their trust and respect; identifies clients’ needs and matches them to appropriate solutions; monitors ongoing developments inside and outside the clients’ environment to keep informed and anticipate problems; keeps clients informed of progress or setbacks in projects; meets timeline for delivery of products or services to client. JUDGEMENT/DECISION-MAKING: Identifies the key issues in a complex situation, and comes to the heart of the problem quickly; gathers relevant information before making a decision; considers positive and negative impacts of decisions prior to making them; takes decisions with an eye to the impact on others and on the Organization; proposes a course of action or makes a recommendation based on all available information; checks assumptions against facts; determines the actions proposed will satisfy the expressed and underlying needs for the decision; makes tough decisions when necessary. EducationAdvanced university degree (Master’s degree or equivalent) in data science, mathematics, statistics, engineering or any related field involving data science is required. A first-level university degree in combination with qualifying experience may be accepted in lieu of the advanced university degree. A degree in data science with a focus on environmental applications is desirable. Job - Specific QualificationNot available. Work ExperienceA minimum of ten years of progressively responsible experience in data science, data analytics, applied mathematics, or software engineering, is required. Experience in statistical and computational methods, such as clustering, classification, correlation, dimension reduction, forecasting, machine/deep learning, and Generative AI is required. Experience in data Science tools such as Jupyter, Matlab, Knime, SPSS, SAS or similar Statistical Programming Languages such as R, Python, Javascript, tools for large datasets such as Hadoop, Spark is required. Experience managing software development and data science teams to deliver production-grade data platforms and applications is required. Experience managing the delivery of environmental applications with an international or multinational setting is desirable. LanguagesEnglish and French are the working languages of the United Nations Secretariat. For this job opening, either English or French is required. The table below shows the minimum required level for each skill in these languages, according to the UN Language Framework (please consult https://languages.un.org for details).