Statistician/Lecturer

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Position Title: Statistician/Lecturer
Location: Tokyo
Country: Japan
Deadline Date: Not specified

Job Details

Job Posting Organization:
The United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) was established to promote sustainable and inclusive development and regional connectivity in the Asian and Pacific region. As a regional development arm of the United Nations Secretariat, ESCAP supports its member states through policy-oriented research, analysis, normative support, technical assistance, and capacity building. The Statistical Institute for Asia and the Pacific (SIAP), a subsidiary body of ESCAP, was founded in May 1970 and is located in Chiba, Japan. SIAP's mission is to enhance the capabilities of developing members and associate members in the region to collect, analyze, and disseminate statistics, thereby supporting economic and social development planning. The Institute plays a crucial role in the overall work programme of the ESCAP Statistics subprogramme, focusing on strengthening statistical training capabilities.

Job Overview:
The Statistician/Lecturer position at the Statistical Institute for Asia and the Pacific (SIAP) involves a range of responsibilities aimed at enhancing statistical training and capacity building in the region. The incumbent will design, plan, and conduct training sessions on various statistical methods and analyses, including data visualization, geospatial statistics, and big data analysis. The role also includes preparing and updating training materials based on international standards and managing the Institute's e-learning management systems. The position requires representation of SIAP in international and regional forums, emphasizing the importance of effective communication and collaboration with stakeholders. The incumbent will be expected to contribute to the development of web-based training courses, particularly focusing on the production and analysis of Sustainable Development Goal (SDG) indicators. This role is pivotal in ensuring that statistical training aligns with the evolving needs of member states in the Asia and Pacific region.

Duties and Responsibilities:
The duties and responsibilities of the Statistician/Lecturer include:

• Designing, planning, and conducting training sessions on statistical methods and analysis, including data visualization, geospatial statistics, and big data analysis.
• Preparing and updating training materials based on international standards and methodological research.
• Managing the Institute's e-learning management systems and leading the design of web-based training courses.
• Representing SIAP in international, regional, and intergovernmental forums.
• Performing other related duties as assigned by the Director and Deputy Director of SIAP.
• Ensuring that training programs are relevant and effective in meeting the needs of developing countries in the region.
• Collaborating with colleagues to achieve organizational goals and fostering a team-oriented environment.

Required Qualifications:
The position requires an advanced university degree (Master's degree or equivalent) in statistics, mathematics, computer science, data science, or a related field. Alternatively, a relevant first-level university degree combined with two years of qualifying experience may be accepted in lieu of the advanced degree. Candidates must possess a minimum of five years of progressively responsible experience in the collection, analysis, and dissemination of statistical data or related areas within national or international statistical systems. Substantive expertise in statistical areas relevant to the responsibilities of the post is essential, including experience in analyzing survey data, big data, geospatial data, and data wrangling using programming languages and statistical packages. Experience in designing and delivering effective statistical training is also required.

Educational Background:
Candidates must hold an advanced university degree (Master's degree or equivalent) in statistics, mathematics, computer science, data science, or a related field. A first-level university degree may be accepted if combined with two years of qualifying experience. This educational background is crucial for understanding complex statistical concepts and methodologies necessary for the role.

Experience:
A minimum of five years of progressively responsible experience in the collection, analysis, and dissemination of statistical data or related areas is required. Candidates should have substantive expertise in statistical areas relevant to the responsibilities of the position, including experience with big data, geospatial data, and statistical training. Experience in utilizing cloud computing platforms, machine learning algorithms, and alternative data sources is also necessary. Proven experience in designing and delivering curriculum on big data, artificial intelligence, machine learning, or data visualization is desirable, as is experience presenting at international conferences or workshops on sustainable development related to data science.

Languages:
Fluency in English is required for this position, as English and French are the working languages of the United Nations Secretariat. Knowledge of another UN official language is considered an advantage, enhancing the candidate's ability to communicate effectively in a diverse environment.

Additional Notes:
The position is funded from extra budgetary resources, with an initial appointment for a period of one year. The extension of the appointment will be subject to annual renewal based on performance, funding availability, and continuation of function, with a maximum term of employment as mandated by the SIAP Statute. The selected candidate will receive a fixed-term appointment limited in accordance with administrative instructions. The United Nations encourages diversity and gender equality within the Secretariat, and women candidates are strongly encouraged to apply. The recruitment process is free of charge, and the United Nations does not charge any fees at any stage of the recruitment process.