Organizational context: The International Organization for Migration (IOM), established in 1951, is a UN-related agency focused on promoting humane and orderly migration. It supports governments and migrants by saving lives, protecting people on the move, and facilitating regular migration pathways. This consultancy role is within the Migration and Displacement Data and Research Analytics Division (MDDRAD), contributing to data analysis and AI-driven insights.
Job purpose: This consultancy aims to leverage advanced data science and AI techniques to enhance IOM's operational capabilities and decision-making. The role involves identifying, curating, and analyzing diverse internal and external datasets, including humanitarian surveys, geospatial data, and unstructured information from traditional and social media. By applying large language models (LLMs), AI-enabled workflows, and machine learning models, the consultant will generate critical insights into migration trends, fill data gaps, and develop forecasts. The purpose is to create AI-driven analytical tools and workflows that support IOM's operations, policy development, and strategic foresight, ultimately contributing to more effective responses to displacement and migration challenges.
Responsibilities: The primary responsibilities include developing an agentic system to consolidate and harmonize IOM's Displacement Tracking Matrix (DTM) data across multiple survey rounds and countries, creating a clean, longitudinal dataset with automated validation checks. This involves identifying common questions, harmonizing responses, and building a scalable system. Additionally, the consultant will develop a roadmap for other high-impact AI projects relevant to IOM's work, such as anticipatory action and strategic foresight. This includes conducting technical overviews of AI projects in other organizations and designing specific AI projects with detailed specifications for data sources, technical approaches, implementation milestones, resource requirements, risk assessments, and deployment pathways.
Education: A Master's degree or Ph.D. in a quantitative field such as computer science, data science, artificial intelligence, statistics, mathematics, or physics from an accredited institution is required. A minimum of five years of progressive professional experience in data science, machine learning, AI, or statistics is also necessary.
Work experience: The role requires at least five years of progressively responsible professional experience in data science, machine learning, artificial intelligence, or statistics. Experience developing AI-enabled applications, statistical modeling, working with geospatial data, databases, and humanitarian or migration data are considered desirable.
Skills: Proficiency in programming languages like Python or R, including machine learning libraries. Experience in developing AI (including LLMs), machine learning, and statistical techniques for real-world problems. Ability to process and analyze complex unstructured datasets. Experience communicating technical results to diverse audiences. Desirable skills include experience with RAG systems, agentic workflows, statistical modeling (regression, classification), geospatial data analysis, databases, and humanitarian/migration data.
Required languages:
Desired languages:
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