Responsibilities
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.
Collects and analyzes data to identify trends or patterns and provide insights through graphs, charts, tables and reports using data visualization methods to enable data-driven planning, decision-making, presentation and reporting.
Competencies
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. The ability to analyze and interpret data in support of decision-making and convey resulting information to management. 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.
Education
An advanced university degree (Master’s degree, or equivalent) in data science, computer science, information management, statistics, public administration, public information, management or a related field 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.
Successful completion of both degree and non-degree programs in data analytics, business analytics or data science programs is desirable.
Work Experience
A minimum of seven (7) years of progressively responsible experience in data science, data analytics, applied mathematics, information management or related area 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.
A minimum of two (2) years or more of experience in data analytics or related area is desirable.
Languages
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.
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