Associate Data Scientist, P2 at United Nations Environment Programme (UNEP)

Responsibilities

•  Assists in the exploration, identification, and acquisition of data sources to determine their suitability for use in decision making and advancing the goals of UNEP. Enables broader use of data sources by applying quality methods to structure, clean, format, parse, and standardize for analytical use.
• Establishes a close working relationship with key clients to leverage the use of data science methods to support their programmatic areas with solutions that assist them in accomplishing their mandates.
• Contributes to the design and develops 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.
• Assists in promoting the use of data science solutions through training and the
• development of products, tools and processes to extend the capabilities of UNEP`s offices.
• Contributes to the design and develops customized visualization and presentation products to reveal the findings of analysis for stakeholders and colleagues, suitable for all forms of production to include briefings, reports, documentation to oversight bodies, interactive interfaces, and publication quality outputs.
• Guides, trains and supervises general service staff in the function.
• Contributes to the collection and analysis of data as well as identification of trends or patterns and provides draft insights through graphs, charts, tables and reports using data visualization methods for data-driven planning, decision-making, presentation and reporting.
• Perform any other duties as may be assigned.

Competencies

• PROFESSIONALISM: Knowledge of the data analysis life cycle from ingest and wrangling to analysis and visualization to present findings. Knowledge of statistical and computational methods, such as clustering, classification, correlation, dimension reduction, forecasting, machine learning, detecting outliers, and regression. 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. 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.
• 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.

Education

• Advanced university degree (Master's degree or equivalent) in data science, mathematics, statistics, engineering, or any related field that includes intensified data analysis in the curriculum is required.
• A first-level university degree in combination with two (2) additional years of qualifying 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 two (2) years of progressively responsible experience in data science, data analytics, applied mathematics, information management or related area.
• (No experience is required for candidates who have passed the United Nations Young Professionals Programme Examination (YPP), the United Nations Competitive Recruitment Examination (NCRE) or the G to P Examination.)
• 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.
• Experience working with multiple stakeholders on digital transformation, ideally in an environmental context, is desirable.
• Experience working in an international organization is desirable.
• A minimum of one (1) year or more of experience in data analytics or related area is desirable (none if successful YPP or P-1 with a related degree).

Languages

• English and French are the working languages of the United Nations Secretariat. For the post advertised, fluency in English is required. Knowledge of another official United Nations language is desirable.