Overview
The role involves designing, developing, and deploying machine learning and computational economics methods applied to socioeconomic data on the Arab region to support analytical depth and inform policymaking.
Key Responsibilities
- Design, train, and validate supervised and unsupervised ML models for nowcasting, forecasting, optimization, anomaly detection, and structural change analysis.
- Apply computational economics methods such as agent-based modeling, CGE frameworks, and microsimulation techniques.
- Implement ETL pipelines for data ingestion, transformation, and integration.
- Develop and maintain reproducible ML experiments using version-controlled pipelines.
- Translate economic research questions into quantitative models.
- Conduct statistical and econometric analyses to validate model outputs.
- Collaborate with economists and data scientists to align ML model design with economic theory.
- Implement RESTful APIs to expose model outputs.
- Ensure model scalability, maintainability, and documentation.
- Prepare technical reports, presentations, and documentation.
Required Experience
- A minimum of 5 years of professional experience in machine learning engineering or a closely related discipline is required.
- Demonstrated experience applying machine learning and statistical methods to structured tabular and time-series data, including time-series modelling, clustering, optimization, or forecasting, is required.
- Familiarity with causal inference methods (e.g., graphical models, causal discovery algorithms) is desirable.
- Experience with MLOps tools, pipeline orchestration (Airflow, Prefect, or equivalent), and experiment tracking is desirable.
- Familiarity with econometric methods and statistical inference is desirable.
- Knowledge of LLMs and their application to economic or social datasets is desirable.
Qualifications
- A bachelor's degree in computer science, data science, applied mathematics, economics, or a related field is required.
- A master's degree in computer science, data science, applied mathematics, economics, or a related field is desirable.
