Responsibilities

• Translate organizational needs into data, analytics and reporting requirements to support decisions, strategies and workflows with data and information.
• Identify, analyze, and interpret trends or patterns, using machine learning techniques, statistical methods to identify relevant features and variables in structured and unstructured sources of information and data.
• Design, implement, and operate UNEP enterprise data platforms, including the establishment of a data governance framework and the development of data pipelines.
• Oversee the full data analytics lifecycle, from requirements and design to the building of analysis, reporting and quality control capabilities.
• Ensure technically sound execution of data analytics projects.
• Collaborate with colleagues across departments to identify data analytics needs and support data-driven projects.
• Translate immediate requirements into prototype solutions and oversee their subsequent full implementation.
• Keep track of trends and developments in data analytics best practices, tools, etc.

Competencies

• PROFESSIONALISM: Knowledge analytical skills with the ability to collect, organize, manage, and disseminate significant amounts of information with attention to detail and accuracy. The ability to analyze, model and interpret data in support of decision-making. Adept at queries, report writing and presenting findings. The ability to oversee and quality-check work completed by other team members. 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 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.
• PLANNING AND 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.
• 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.

Education

• Advanced university degree (Master’s degree or equivalent) in computer science, data science, analytics, engineering, statistics, or a related field is required.
• A first level university degree in combination with two (2) additional years of relevant qualifying experience may be accepted in lieu of the advanced university degree.

Work Experience

• A minimum of seven (7) years of progressively responsible experience in applied analytics, data science, business intelligence, statistics, project management, or related area is required.
• Experience in developing digital solutions using data, artificial intelligence and machine learning techniques to advance decisions, strategies and execution is required.
• Experience in designing data integration and pipeline architectures which must include ingesting data through different methods such as message queues, database connections, files, or Application Programming Interface (APIs), is required. Experience with self-service analytics and data visualization applications (MS PowerBI, Qlik, Tableau or similar), or business intelligence tools (SAP Business Objects, etc.) is desirable.
• Experience in DevOps tools chains consisting of tools like Git, Jenkins, Bamboo or equivalent is desirable.
• Experience with data science tools and programming languages (SQL, Python, R) is desirable.
• Experience in delivering big data use cases is desirable, including projects using technology such as Apache Spark, Hadoop or others.