WILDLABS
World Wide Fund for Nature/ World Wildlife Fund (WWF)
The 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. Access the full job posting here.
- Studies, explores, and evaluates new and existing data sources to determine their effectiveness and accuracy for use in decision making, and assess their suitability for actionable output. Provide data-driven recommendations to stakeholders.
- Develops, implements and evaluates assigned programmes, monitors and analyzes their development and implementation, and drafts and reviews relevant documents and reports.
- Designs and builds predictive data science products, such as visualizations, models or AI/ML algorithms for initial simulations or prototypes and subsequent ingestion into mainstream software applications.
- Liaises with technology stakeholders to access infrastructure, software and services needed to develop and deploy data science products.
- Promotes use of data science solutions by showcasing the products to stakeholders; disseminating of data products, and raising awareness of available data products.
- Develops products, tools and processes to periodically validate the effectiveness of data science products and their expected and observed benefits. Assesses impact on business defined key performance indicators; Iteratively improves products based on findings.
- Engages in complex research and analyses to develop data products; uses internal and publicly available data and information.
- Oversees and allocates resources to the building of analysis, reporting and quality control capabilities, contributes to short- and long-term planning of UNEP and assists in identifying threats and opportunities to the successful implementation of its mandate. • Coordinates with different functional teams to implement models and monitor outcomes and translate organizational needs into analytics and reporting requirements to support decisions, strategies and workflows with data and information.
- Develops processes and tools to monitor and analyze model performance and data accuracy and conduct full data analytics lifecycle analysis, including data requirements, activities and design.
- PROFESSIONALISM: Knowledge of data analysis life cycle 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.
- TEAMWORK: Works collaboratively with colleagues to achieve organizational goals. Solicits input by genuinely valuing others’ ideas and expertise; is willing to learn from others. Places team agenda before personal agenda. Supports and acts in accordance with final group decision, even when such decisions may not entirely reflect own position. Shares credit for team accomplishments and accepts joint responsibility for team shortcomings.
- 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.
- 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.
An advanced university degree (Master’s degree, or equivalent) in data science is required. A first-level degree (Bachelor’s degree or equivalent) in the specified fields of studies with two (2) additional years of relevant work experience may be accepted in lieu of the advanced university degree.
A minimum of (7) seven years of progressively responsible experience in data science is required. Experience in using data to advance decisions, strategies and execution is required. Experience managing small teams is required. Experience of working with international multi-agency projects, ideally in an environmental context is desirable. Experience of data science tools such as Jupyter, Matlab, Knime, SPSS, SAS, or similar Statistical Programming Languages such as R, Python, Javascript or related is desirable.
English and French are the working languages of the United Nations Secretariat. For the position advertised, fluency in English is required. Knowledge of another official United Nations language is desirable. NOTE: ''Fluency'' equals a rating of ''fluent'' in all four areas (read, write, speak, understand) and ''Knowledge of'' equals a rating of ''confident'' in two of the four areas
Evaluation of qualified candidates may include an assessment exercise which may be followed by competency-based interview.
View the full job posting here.