WBG Pioneer -Financial Data Engineering Intern

The World Bank Group is offering an internship program called WBG Pioneers, designed for undergraduate and postgraduate students to gain hands-on experience in global development. The Financial Data Engineering Intern will work on designing and prototyping machine learning-based anomaly detection capabilities to enhance data quality within financial operations.

What you'll do:

• Conduct a structured analysis of historical IDA data flows, including replenishment cycles, disbursement patterns, and associated metadata, to identify key signals and failure modes relevant to anomaly detection
• Design and train a lightweight, interpretable anomaly detection model using appropriate machine learning approaches (e.g., Isolation Forest, Autoencoders, or statistical process control methods), calibrated to the sensitivity requirements of financial data. Document model assumptions, feature engineering decisions, and evaluation metrics in a clear and reproducible manner
• Integrate the trained model into an automated data pipeline leveraging Azure cloud services (e.g., Azure Data Factory, Azure Machine Learning, or Azure Databricks), in alignment with ITSFE's existing infrastructure
• Develop alerting or flagging mechanisms that surface detected anomalies to data engineers and financial analysts in a timely and actionable format
• Ensure the solution adheres to WBG data governance standards and security protocols
• Participate fully in ITSFE's Agile ceremonies, including sprint planning, daily standups, sprint reviews, and retrospectives
• Present progress and prototype demos to unit stakeholders, showcasing how predictive capabilities improve data governance and reduce manual validation overhead
• Collaborate with data engineers, financial analysts, and technical leads to refine requirements and validate model outputs against real-world expectations
• Produce technical documentation covering the model architecture, pipeline integration design, and operational guidelines for handoff to the engineering team
• Prepare a final presentation summarizing findings, methodology, and recommendations for scaling or productionizing the solution

What they're looking for:

• Candidates must be currently enrolled in, or in the final year of postgraduate program in Engineering
• Candidates must have 0–6 years of relevant professional experience
• Academic background must align with the requirements outlined in the job description
• Strong statistical background, including understanding of probability distributions, time-series analysis, and anomaly detection methodologies
• Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Proficiency in Python and data manipulation tools (pandas, NumPy, SQL)
• Familiarity with cloud-based data engineering concepts, preferably on Azure
• Intellectually curious with a genuine interest in applying AI to high-impact, real-world financial systems
• Demonstrated interest in development work and the World Bank Group's mission
• Strong analytical, research, and problem-solving skills