Consultancy - Data Scientist, Berlin, Germany

## Consultancy - Data Scientist, Berlin, Germany - Organization:IOM - International Organization for Migration - Office:IOM Global Migration Data Analysis Centre Established in 1951, IOM is a Related Organization of the United Nations and the leading UN agency in the field of migration. Working closely with governmental, intergovernmental and non-governmental partners, IOM promotes humane and orderly migration for the benefit of all. It saves lives and protects people on the move, drives solutions to displacement, and facilitates pathways for regular migration, while providing services and advice to governments and migrants. IOM is committed to fostering a respectful, inclusive and supportive workplace where all employees can thrive professionally and feel valued. By creating such an environment, IOM aims to better harness the full potential of migration and strengthen its support to people on the move. IOM invites candidates from diverse backgrounds to apply and provides reasonable accommodation throughout the recruitment process when required. Learn more about IOM's workplace culture at IOM workplace culture | International Organization for Migration Project Context and Scope This consultancy supports the Migration and Displacement Data and Research Analytics Division (MDDRAD). The scope of work includes: - Identify, compile, and curate internal and external datasets with operational relevance to IOM. These range from humanitarian surveys (e.g., collected through IOM's Displacement Tracking Matrix (DTM)), to geospatial datasets of environmental and socio-economic variables, to unstructured data from traditional and social media. - Use large language models (LLMs) and other AI methods to process, structure, analyze, and synthesize structured and unstructured data. Develop AI-enabled analytical workflows and decision-support tools, including using approaches such as retrieval-augmented generation (RAG) and agentic systems. - Develop machine learning and statistical models (including regression and classification) to generate insights relevant for IOM operations, policy, and decision-making. Conduct analyses to identify trends and patterns, fill data gaps, and develop forecasts. - Communicate analytical products through visualizations, presentations, and reports tailored to audiences with varying levels of technical expertise. - Collaborate with data, research, policy, and operational colleagues across IOM, as well as with governments, UN agencies, academia, NGOs, and private-sector partners. Organizational Department / Unit to which the Consultant is contributing Migration and Displacement Data and Research Analysis Division, DDIP. Tasks to be performed under this contract 1. AI-driven consolidation of DTM data across rounds (2 months) 1.1 Implementation of an agentic system that (i) identifies questions shared across DTM surveys conducted at multiple points in time, (ii) harmonizes these questions and their answers (which differ in phrasing, format, ...), (iii) builds a clean, longitudinal dataset combining all available survey times, (iv) includes thorough automatic sanity checks as well as human-in-the-loop validation - beginning with the use case of Mobility Tracking surveys in selected pilot countries. 1.2. Compilation of analogous data from DTM operations outside pilot countries, and development of a clear roadmap on how to generalize the system to these use cases. 2. Roadmap for additional AI projects with high potential operational impact (1 month) 2.1. Development of a technical overview of relevant AI projects conducted in other UN agencies, government bodies, international organizations, and NGOs, relevant to IOM's work. 2.2. Identification and detailed design of one or more high-impact AI projects for IOM's operational data work (e.g., on Anticipatory Action or Strategic Foresight), with clearly specified and validated data sources, technical approaches, implementation milestones, resource requirements, risk assessments, and pathways to operational deployment. Performance indicators for the evaluation of results Performance will be evaluated against the following indicators: - Timely delivery of outputs:All agreed deliverables are submitted within agreed timeframes and meet the defined specifications. - Technical quality and methodological rigor:Outputs demonstrate strong analytical validity, transparent assumptions, and appropriate use of quantitative and remote-sensing methods. - Usability for decision-making:Analytical products are decision-oriented, clearly articulated, and usable for anticipatory action, preparedness, or strategic discussions. - Scalability and institutional value:Methodologies, workflows, and guidance developed can be applied across multiple country contexts and contribute to longer-term MDDRAD analytical capacity. - Ethical compliance:Remote-sensing and analytical outputs reflect responsible data use and alignment with UN data responsibility principles. - Effective collaboration:Evidence of constructive engagement with internal teams and external partners, including delivery of joint analytical outputs where applicable. Required Qualifications and Experience - Master's degree or Ph.D. in computer science, data science, artificial intelligence, statistics, mathematics, physics, or a related quantitative field from an accredited academic institution. - A minimum of five years of progressively responsible professional experience in data science, machine learning, artificial intelligence, statistics, or a related field. Proficiency in one or more scientific programming languages such as Python or R, including machine learning libraries. - Experience developing artificial intelligence (including LLMs), machine learning, and/or statistical techniques to solve real-world analytical problems. - Demonstrated ability to process and analyze complex unstructured datasets. - Experience communicating technical results to technical and non-technical audiences. - Experience developing AI-enabled applications, such as retrieval-augmented generation (RAG) systems, agentic workflows, or other decision-support tools.Experience with statistical modelling, including nonlinear regression and classification (e.g., using random forests, gradient boosting, neural networks).Experience working with geospatial data and spatial analysis.Experience with databases and data engineering tools, including SQL and cloud-based platforms.Experience working with humanitarian or migration data. - Experience with statistical modelling, including nonlinear regression and classification (e.g., using random forests, gradient boosting, neural networks). - Experience working with geospatial data and spatial analysis. - Experience with databases and data engineering tools, including SQL and cloud-based platforms. - Experience working with humanitarian or migration data. Required Competencies IOM's competency framework can be found at this link. Competencies will be assessed during the selection process. Values- all IOM staff members must abide by and demonstrate these five values: - Inclusion and respect for diversity: Respects and promotes individual and cultural differences. Encourages diversity and inclusion. - Integrity and transparency: Maintains high ethical standards and acts in a manner consistent with organizational principles/rules and standards of conduct. - Professionalism: Demonstrates ability to work in a composed, competent and committed manner and exercises careful judgment in meeting day-to-day challenges. - Courage: Demonstrates willingness to take a stand on issues of importance. - Empathy: Shows compassion for others, makes people feel safe, respected and fairly treated. Core Competencies- behavioral indicators - Teamwork: Develops and promotes effective collaboration within and across units to achieve shared goals and optimize results. - Delivering results: Produces and delivers quality results in a service-oriented and timely manner. Is