Data Management Officer/Senior Data Management Officer (STA) (Contractual)

Overview

Support data management and governance in the Statistics Department

You have:

• An advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background; alternatively, a bachelor's degree in data science, statistics, economics, finance, and/or related discipline supplemented by a minimum of six years of relevant professional experience is required.
• For Data Management Officer: In addition to an advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background, at least 2 years of relevant professional experience is required.
• For Senior Data Management Officer: In addition to an advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background, at least 4 years of relevant professional experience is required.
• Experience with the application of statistical data management principles, concepts, techniques and methods;
• Strong understanding of metadata management and how it can be aligned with user's needs for better discovery and retrieval of data.
• Knowledge of current and emerging technologies around data management systems and tools.
• Knowledge of the suite of models and standards developed and maintained by the international statistical community, such as the GSBPM and the GSIM, and of other international standards, particularly SDMX, is desirable.
• Experience in data/metadata modelling (subject area, conceptual) and managing data glossaries would be a distinct advantage.
• Knowledge of one or more mainstream programming language for data analytics (R, Python, Java, etc.) would also be an asset.
• The successful candidate should have an analytical mindset, with keen attention to detail and proven problem-solving skills.
• Should have a strong drive for results, with the ability to effectively prioritize and adjust quickly to changing priorities.
• Client-oriented, with excellent inter-personal skills and the ability to work well with a team of diverse staff in a highly collaborative environment.
• Strong written and oral communication skills, including proven ability to communicate and explain complex issues in clear, concise and persuasive language.

Work for the IMF. Work for the World.

Typically Reports to:

Section Chief, Deputy Division Chief, Division Chief

Job Summary

The Statistics Department (STA) provides global leadership on statistical methodologies and standards for the Fund, its member countries, and the international statistical community. It supports Fund surveillance and lending operations to strengthen member countries’ capabilities to produce and disseminate macroeconomic and financial statistics for sound policy-making. STA collaborates with other Fund departments, donors, and other external partners to ensure that data needs for bilateral and multilateral surveillance and lending operations are met. Under the aegis of the Overarching Strategy on Data and Statistics, the department also takes the lead in improving data management outcomes and in promoting data innovation.

The Statistics Department has an opening in its Data Governance and Services division for a Data Management Officer/Sr. Data Management Officer. Under the supervision of the Division Chief and the two Deputy Division Chiefs, the Data Management Officer/Sr. Data Management Officer supports the design activities related to the ingestion, validation, processing, aggregation/calculation, and dissemination of economic data and metadata collected by the Statistics Department. The Data Management Officer/Sr. Data Management Officer also supports the internal data governance bodies and the implementation of their related work programs. Furthermore, the Data Management Officer/ Sr. Data Management Officer may liaise with the Information Technology Department (ITD) to ensure existing technologies support the Fund’s data management objectives, in consultation with STA’s Data Operations division, as needed.

Specific duties and responsibilities include but are not limited to:

• Support the Data Governance Group, the Fund wide group focused on improving data management outcomes, in the formulation of principles for strengthening data management practices across the Fund and in the implementation of its work program. In particular, s/he works toward convergence of departmental data management practices, including the emergence of institution-wide standards for statistical data and metadata;
• Assist with the design of an institution-wide metadata model by developing metadata structures;
• Contribute to the development and implementation of coding standards for external data exchange and consumption, particularly in the context of the implementation of the Fund’s Data Dissemination Initiatives (i.e. e-GDDS, SDDS, SDDS+);
• Contribute to design activities (business and data requirements) to enhance existing STA data products and develop new ones, following specifications provided by data owners;
• Collaborate with ITD to ensure alignment of metadata structures with ongoing systems activity and develop requirements for data collection, management, and dissemination systems, liaising with STA’s Data Operations division;
• Participate in data analytics activities of the division as needed, such as data visualization and analysis of usage statistics.

Qualifications

• An advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background; alternatively, a bachelor’s degree in data science, statistics, economics, finance, and/or related discipline supplemented by a minimum of six years of relevant professional experience is required.
• For Data Management Officer: In addition to an advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background, at least 2 years of relevant professional experience is required.
• For Senior Data Management Officer: In addition to an advanced degree in data science, statistics, economics, finance, and/or related discipline with a strong quantitative and computational background, at least 4 years of relevant professional experience is required.

In addition to the minimum qualifications described above, the candidate should also possess:

• Experience with the application of statistical data management principles, concepts, techniques and methods;
• Strong understanding of metadata management and how it can be aligned with user’s needs for better discovery and retrieval of data;
• Knowledge of current and emerging technologies around data management systems and tools;
• Knowledge of the suite of models and standards developed and maintained by the international statistical community, such as the GSBPM and the GSIM, and of other international standards, particularly SDMX, is desirable.

Experience in data /metadata modelling (subject area, conceptual) and managing data glossaries would be a distinct advantage. Knowledge of one or more mainstream programming language for data analytics (R, Python, Java, etc.) would also be an asset.

The successful candidate should have an analytical mindset, with keen attention to detail and proven problem-solving skills. S/he should have a strong drive for results, with the ability to effectively prioritize and adjust quickly to changing priorities. S/he should be client-oriented, with excellent inter-personal skills and the ability to work well with a team of diverse staff in a highly collaborative environment. In addition, s/he should have strong written and oral communication skills, including proven ability to communicate and explain complex issues in clear, concise and persuasive language.

Department:

STADS Statistics Department Data Governance and ServicesHiring For:

A09, A10, A11The IMF is committed to achieving a diverse staff, including age, creed, culture, disability, educational background, ethnicity, gender, gender expression, nationality, race, religion and beliefs, and sexual orientation.

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Potential interview questions

Added 3 years ago - Updated 1 year ago - Source: imf.org