Computational Economics Expert/Sr. Computational Economics Expert

The Computational Economics Expert provides Fund-wide advanced quantitative solutions combining computational economics, econometric and machine learning modeling, and modern data engineering. The role involves designing and implementing integrated solutions across economic, quantitative, computational, and data dimensions to support the Fund’s surveillance, lending, and capacity development business capabilities.

Responsibilities

• Collaborate with business and technical stakeholders to define requirements, identify appropriate data and analytical approaches, and develop, implement, validate, and maintain quantitative, statistical, machine learning, and economic modeling solutions that address business and research needs.
• Research and develop methodologies, algorithms, software components, and reusable analytical tools to address complex quantitative and computational challenges and enhance the Fund’s analytical capabilities.
• Design, develop, and maintain scalable data pipelines, integration solutions, and data platforms that support the efficient acquisition, transformation, storage, delivery, and analysis of large-scale structured and unstructured data across diverse business and technology environments.
• Ensure the quality, reliability, and operational efficiency of data services by analyzing and resolving data issues, integrating data from multiple sources, optimizing data delivery processes, and implementing automation and other continuous improvements.
• Develop, and optimize algorithms, computational models, and software solutions that enhance analytical capabilities, performance, scalability, and reproducibility, utilizing appropriate programming languages, tools, and modern software engineering practices.
• Develop and maintain shared analytical platforms, reusable software components, and computational environments, while promoting standards, governance, and best practices that support efficient, reliable, and scalable data and analytical workflows.
• Monitor developments in data science, machine learning, computational methods, and related fields; evaluate emerging technologies and methodologies; and provide expert guidance on analytical, computational, and data architecture challenges to support Fund business needs.
• Develop technical documentation, sample applications, tutorials, presentations, and training materials, and communicate complex technical concepts effectively to business stakeholders, technical teams, and other audiences.

Requirements

• Advanced degree in Computer Science, Economics, Engineering, Applied Mathematics, or relevant field plus a minimum of four (4) years of post-graduation professional experience, or a bachelor’s degree plus a minimum of ten (10) years of post-graduation professional experience is required.
• Deep expertise in data engineering and architecture, with extensive experience designing, building, and managing scalable data pipelines, integrated data platforms, and cloud-based data solutions.
• Strong understanding of mathematical, numerical, and optimization methods, with experience developing algorithms and solving complex analytical problems.
• Knowledge of econometric methods and economic models, with experience applying quantitative techniques to analyze and forecast economic outcomes.
• Knowledge of machine learning and statistical learning methods, with experience applying them to data analysis and predictive modeling.
• Proficiency in scientific computing and programming languages, with experience developing reliable, reusable, and reproducible analytical solutions.
• Demonstrated ability to define and solve complex problems under uncertainty while collaborating effectively with multidisciplinary teams.
• Strong communication skills, with the ability to explain technical concepts clearly and develop effective knowledge-sharing materials.

Skills

• Data Engineering
• Data Architecture
• Scalable Data Pipelines
• Integrated Data Platforms
• Cloud-based Solutions
• Mathematical Methods
• Numerical Analysis
• Optimization Techniques
• Algorithm Development
• Econometric Techniques
• Economic Modeling
• Quantitative Analysis
• Forecasting
• Machine Learning
• Statistical Learning
• Scientific Computing
• Programming
• Analytical Solution Development
• Problem Solving under Uncertainty
• Technical Communication

Languages

English