Data Analytics Officer / Senior Data Analytics Officer - STADS (Contractual)

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Application deadline 2 months ago: Thursday 29 Feb 2024 at 23:59 UTC

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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 policymaking. 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.

The Statistics Department has an opening in its Data Governance and Services division for a Data Analytics Officer/Sr. Data Analytics Officer position. Under the supervision of the Division Chief and the two Deputy Division Chiefs, the Data Analytics/Sr. Data Analytics Officer support the evaluation of economic data to increase utility to its end-users. The primary responsibility is to help distill large amounts of data from varied sources to support the needs of Fund stakeholders, increase data quality, and present analytical results in innovative ways. Additionally, the Officer leverages statistical tools and analytical methods to evaluate economic data for integrity, utility, and fit-for-purpose for the Department and Fund users. Furthermore, the Officer liaises with data producers and data users to develop new data products to fit the changing needs of data consumers and develop innovative ways to collect new data.

The main responsibilities of the Data Analytics Officer include but not limited to:

  • Transform, filter, and clean large and complex datasets in a manner that is suitable for analysis.
  • Contribute to the development of new data products and enhancement of existing STA data products. Identify, analyze, and interpret trends and patterns in economic data and its usage to produce new insights and analytical products.
  • Support analytical work in proof of concepts and research projects using Big Data sources. Uncover alternative sources of data (including tools and methods to collect data digitally), evaluate ways to integrate existing data, and assess data definitions for meeting data needs.
  • Visualize and report analytical findings using a variety of methods to promote understanding of key insights for both technical and non-technical audiences.
  • Engage a diverse audience through written and spoken communications, including to obtain and disseminate data, promote events, and manage website content relevant to the activities of the Division.
  • Assist in leveraging methods from diverse disciplines (e.g., machine learning, statistical modeling, data mining, natural language processing) to improve data collection and data quality of datasets maintained by the Department.
  • Support data architecture decisions and collaborate with technology teams to implement models/algorithms in production systems to improve data elements needed to support business objectives and dissemination methods for the Department.
  • Maintain existing relationships with data end users to assess business needs and maximize fit-for-purpose utility of the Fund’s data. Identify potential for recurring products through collaboration with data users to develop value added products.

Qualifications

Minimum qualifications include educational development typically acquired through the completion of a master's degree, or equivalent, in economics, statistics, information management, data management, computer science, or a related field of study; or a bachelor's degree in one of these fields or a related field, supplemented by six years of relevant professional experience.

In addition, the candidates should possess:

  • Knowledge of multivariate analysis, statistical modeling, econometrics, time series analysis, and/or other statistical techniques in economics, or similar domains.
  • Knowledge of machine learning techniques, economic modeling, and forecasting techniques.
  • Experience working with large data sets and Big Data tools and stack (e.g., Hadoop and Spark).
  • Experience with modeling tools (e.g., STATA, SAS, R, MATLAB) and one or more mainstream programming language (Python, Java, C, C++, etc.).
  • Strong knowledge of relational database principles (e.g., SQL).
  • Strong ability to produce compelling and dynamic visualization using different types of datasets.
  • Knowledge of macroeconomic and financial concepts, including related to climate and gender issues, and key data series used in Fund operations; solid knowledge of data-related Fund operations would also be an asset.
  • Strong written and oral communication skills, including proven ability to communicate and explain complex issues in clear, concise and persuasive language as well as to effectively promote and articulate event details in a clear and compelling manner.
  • Strong user-orientation, and ability to work well with a team of diverse staff in a collaborative environment.
  • Strong drive for results; ability to effectively prioritize, adjust quickly to changing priorities and execute while under pressure.
  • Strong interpersonal skills, including the ability to influence, negotiate and resolve conflict.

This is a one-year contractual appointment. Contractual appointments at the IMF are renewable for up to four years of cumulative contractual service, pending incumbent's performance, budget availability, and continuous business need.

The IMF is committed to achieving a diverse staff, including gender, nationality, culture and educational background.

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. We welcome requests for reasonable accommodations for disabilities during the selection process.

Added 2 months ago - Updated 2 months ago - Source: imf.org