Machine Learning Engineer

Client of United Nation careers

The Machine Learning Engineer will be responsible for the following tasks:

1. Machine Learning Model Development

• Design, train, and validate supervised and unsupervised ML models on socioeconomic datasets, with applications in nowcasting, forecasting, optimization, anomaly detection, and structural change analysis.
• Apply computational economics methods such as agent-based modeling, computable general equilibrium (CGE) frameworks, microsimulation techniques, and other quantitative approaches relevant to the unit's projects. Implement ETL pipelines for data ingestion, transformation, and integration from multiple sources including national statistics, UN databases, and open data platforms.
• Develop and maintain reproducible ML experiments using version-controlled pipelines (MLflow equivalent).

2. Economic Data Analysis and Modeling

• Translate economic research questions into quantitative models that leverage large-scale structured and semi-structured datasets.
• Conduct statistical and econometric analyses to validate model outputs and provide confidence intervals, sensitivity analyses, and scenario projections.
• Collaborate with economists and data scientists to align ML model design with economic theory and regional development frameworks.

3. API Integration and Technical Infrastructure

• Implement RESTful APIs to expose model outputs and integrate with the different ecosystems.
• Ensure model scalability, maintainability, and documentation for handoff and long-term institutional use.

4. Collaboration and Reporting

• Collaborate with cross-functional teams including economists, data scientists, and software developers to align data strategies and analytical outputs.
• Prepare technical reports, presentations, and documentation explaining methodologies, findings, and model performance to both technical and non-technical audiences.