Task description
Under the direct supervision of a Data Specialist in Enterprise Solutions Section/UN Environment’s Corporate Services Division, the UN Volunteer will take the following tasks:
Development of an analytical solution for the Global Climate Fund Unit
Draft requirements documents based on the unit needs.
Understand/explore required datasets, assess existing dashboard, and conceptualize new or improved design and new features.
Develop dashboard based on the requirements.
Develop a risk management component to flag critical projects with respect to the timeline, fees consumption, etc.
Develop a country profiles component to enable GCF team members to have an overview of ongoing and planned projects (GCF and others) in each country and perform analysis by sector and other parameters to inform project proposal design.
Explore applications of LLMs, including prototyping a Chatbot that users can use to query the projects data and supporting them in the drafting of new project proposals.
Provide trainings and support the GCF team in using the dashboard.
Assist with other data-related activities
Assist in the design and development of other data science products that requires the ap-plication 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.
Assist in the exploration, identification, and acquisition of data sources to determine their suitability for use in decision making and advancing the goals of the organization.
Research on new AI and ML applications and assist in promoting the use of data science solutions through webinar and training.
Any other related tasks as may be required or assigned by the supervisor.
Furthermore, UN Volunteers are encouraged to integrate the UN Volunteers programme mandate within their assignment and promote voluntary action through engagement with communities in the course of their work. As such, UN Volunteers should dedicate a part of their working time to some of the following suggested activities:
Strengthen their knowledge and understanding of the concept of volunteerism by reading relevant UNV and external publications and take active part in UNV activities (for instance in events that mark International Volunteer Day).
Be acquainted with and build on traditional and/or local forms of volunteerism in the host country.
Provide annual and end of assignment self-reports on UN Volunteer actions, results, and opportunities.
Contribute articles/write-ups on field experiences and submit them for UNV publications/websites, newsletters, press releases, etc.
Assist with the UNV Buddy Programme for newly arrived UN Volunteers.
Promote or advise local groups in the use of online volunteering or encourage relevant local individuals and organizations to use the UNV Online Volunteering service whenever technically possible.
Eligibility criteria
Age
18 – 26
Nationality
Candidate must be a national of a country other than the country of assignment.
Requirements
Required experience
1 years of experience in data science, data analytics, applied mathematics, information management or related area is required.
Experience in using data and machine learning models to advance decisions and strategies is required.
Experience with SQL and Python, and with self-service analytics platforms (MS PowerBI, Qlik, Tableau or similar) is required.
Experience in tools managing version control such as Git is highly desirable.
ability to work and adapt professionally and effectively in a challenging environment; ability to work effectively in a multicultural team of international and national personnel.
self-motivated; ability to work with minimum supervision; ability to work with tight deadlines.
Have affinity with or interest in environmental issues, volunteerism as a mechanism for durable development, and the UN System.
Area(s) of expertise
Economics and finance, Engineering and construction
Driving license
–
Languages
English, Level: Fluent, Required
Required education level
Master degree or equivalent in Data Science, Mathematics, Statistics, Engineering, or any related field that includes data science in the curriculum.
Competencies and values
Accountability
Client Orientation
Creativity
Professionalism
Technological Awareness
Working in Teams
Deadline : Dec 14, 2023
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