Data Scientist

Job purpose

The Data Scientist role is focused on building advanced analytics capabilities that strengthen the Arab Monetary Fund’s research, policy analysis, and decision-making. This position uses machine learning, artificial intelligence, and statistical methods to uncover insights, improve data integration, and support innovation across the organization.

Key responsibilities

• Develop and deploy statistical models, machine learning methods, and AI-based tools for large structured and unstructured datasets.
• Run predictive and prescriptive analytics to support economic and financial policy work.
• Improve model performance, reliability, and scalability over time.
• Prepare, clean, transform, and organize multiple data sources through automated ETL workflows.
• Work with the IT team to strengthen data infrastructure for secure and efficient access.
• Maintain data quality and ensure solutions follow the organization’s data architecture standards.
• Support research teams with data-driven work on emerging areas such as digital economy, AI, climate, and financial innovation.
• Use advanced approaches including deep learning and natural language processing to support research output.
• Track developments in the data science field and introduce relevant new methods and tools.
• Create dashboards and visual presentations that translate findings for policymakers.
• Develop data storytelling materials for publications, policy discussions, and training sessions.
• Ensure data is presented consistently and accessibly across reports and platforms.
• Follow data protection rules, internal policies, and ethical AI principles.
• Help implement data governance processes and quality controls.
• Take part in audits and compliance checks related to data access and usage.

Experience and qualifications

The role requires at least 5 years of professional experience in data science, machine learning, and advanced analytics, ideally in economic, financial, or public policy environments. The candidate should have a strong track record of building predictive models and turning analysis into practical recommendations.

Education

A bachelor’s degree in data science, computer science, statistics, economics, or a closely related discipline is required.

Preferred certifications

Helpful certifications include Google Data Analytics, IBM Data Science, SAS, and CAP (Certified Analytics Professional).