Data analyst

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Description

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• Engage in data cleaning and preparation for analyses and explore it for insights. 
• Build routines to manipulate and transform the SDW inputs and automatize the transfer of data inputs from various data sources and formats.
• Create multiple modalities of the data analyses, in close consultation with the FAO data producers and the front-end development team.
• Translate statistical datasets into information and knowledge using data visualizations and data analysis tools.
• Utilize data analytics tools to draw insights and transform complex data into actionable narratives.
• Conduct quality checks of disseminated data and metadata outputs in compliance with statistical standards and prepare reports on the quality.
• Develop routines for automatic data reporting and exchange from the FAODATA Explorer to other platforms.

• University degree in Statistics, Data Sciences, Computer Sciences, Data Management or related disciplines.
• At least three years of years of relevant experience in collecting, manipulating, analysing and disseminating significant amounts of statistical data with attention to detail and accuracy. 
• Working knowledge (level C) of English and limited knowledge (level B) of another of the languages (Arabic, Chinese, French, Russian, Spanish) are required. For PSA subscribers only working knowledge of English is required.

• Extent of knowledge and relevant experience in the use of R and/or Python for data analysis.
• Extent of knowledge and relevant experience in relational databases, database design and database systems like MySQL, PostgreSQL or MS SQL is desirable. 
• Extent of knowledge of and relevant experience in User Experience Design, with an emphasis in the design and implementation of user-oriented experience for digital products.
• Extent of knowledge and relevant experience in data visualizations using Tableau and/or Power BI. 
• Knowledge of the Statistical Data and Metadata eXchange (SDMX) standard and compliant tools will be an asset. 
• Ability to deploy data-driven analyses and deploy systematic and logical approach to problem-solving. 
• Ability to work independently, with minimum supervision.

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