Data Scientist

Job Posting Organization:
The job posting organization is a collaborative initiative between UNHCR (United Nations High Commissioner for Refugees) and DRC (Danish Refugee Council), focusing on regional protection monitoring across West and Central Africa. This initiative, known as Project 21 (P21), aims to enhance evidence-based protection responses in displacement-affected contexts. The organization is dedicated to mobilizing humanitarian partners to collect and analyze protection data, ensuring that responses are informed by accurate and timely insights. The complexity of the humanitarian challenges addressed under P21 necessitates a robust data science approach to transform raw data into actionable intelligence. The organization operates in multiple countries across West and Central Africa, emphasizing the importance of collaboration and innovation in addressing the needs of displaced populations.

Job Overview:
The scientist" style="border-bottom: 1px dotted #007bff !important;">Data Scientist position is integral to Project 21, where the individual will play a crucial role in building a predictive machine learning model that integrates various datasets to infer protection risks and humanitarian needs. The role is split between innovation and mainstream activities, with 50% of the time dedicated to developing the predictive model in collaboration with various teams, including the Project Lead, UNHCR data scientists, and the Protection Unit. The Data Scientist will be responsible for designing statistical methodologies, implementing machine learning algorithms, and ensuring data quality and compliance with UNHCR standards. This position requires a strong analytical mindset to transform complex datasets into meaningful insights that can guide humanitarian interventions, especially in regions with limited access due to conflict or displacement. The Data Scientist will also support ongoing protection monitoring activities, applying data science techniques to identify trends and inform proactive protection strategies.

Duties and Responsibilities:
The Data Scientist will have a comprehensive set of responsibilities, including:

• Data Acquisition and Integration: Collecting, cleaning, and harmonizing datasets from various sources such as ACLED, WFP, and UNHCR, ensuring data quality and compliance with protection standards.
• Model Development: Designing and implementing predictive models using machine learning techniques, training and validating these models with historical and real-time data, and maintaining reproducible workflows.
• Composite Indices Construction: Developing algorithms for data imputation and constructing vulnerability indicators to address gaps in data from conflict-affected areas.
• Pilot Testing and Evaluation: Deploying the predictive model for pilot testing, comparing predictions with field data, and refining the model based on feedback.
• Geospatial Analysis and Visualization: Collaborating with teams to create user-friendly visualizations, such as dynamic risk maps and dashboards.
• Capacity Building: Conducting training sessions for UNHCR staff and partners, developing user guides and standard operating procedures for model deployment.
• Ethical and Risk Management: Implementing safeguards to prevent misuse of predictive outputs and ensuring transparency in model operations.
• Monitoring and Progress Controls: Defining objectives with supervisors, producing regular reports, and delivering key outputs such as harmonized datasets and predictive models with performance metrics.

Required Qualifications:
The ideal candidate for the Data Scientist position will possess a strong foundation in survey methodology, including experience in designing questionnaires and conducting surveys in challenging environments. A deep understanding of statistical concepts and methods is essential, along with experience in data sharing, anonymization, and management. Proficiency in data visualization tools such as D3.js, Power BI, or Tableau is required. Candidates should have prior experience in protection monitoring and socio-economic data analysis, particularly in the context of West and Central Africa. Capacity building skills and the ability to provide technical support to data-related functions within UNHCR and its partners are also important. The candidate should demonstrate a strong quantitative background and experience in data collection, management, and applied analysis using statistical software or programming languages.

Educational Background:
Candidates must hold an advanced university degree (master’s or PhD) in Data Science, Statistics, Computer Science, Applied Mathematics, Computational Social Sciences, or a related quantitative field. This educational background is critical for understanding the complex analytical tasks required in this role and for effectively contributing to the development of predictive models and data-driven insights.

Experience:
For this position, candidates should have relevant work experience that aligns with the level of the role. Specifically, for P2/NOB level, candidates should have at least 3 years of relevant experience with an undergraduate degree, 2 years with a graduate degree, or 1 year with a doctorate. This experience should include practical application of data science techniques in humanitarian or development contexts, particularly in relation to forced displacement and protection monitoring.

Languages:
The mandatory language for this position is English, with French being a desirable language. Proficiency in both languages will enhance communication and collaboration within the diverse teams involved in the project and with external partners.

Additional Notes:
This position is classified under the UNOPS IICA1 staff member type and is not remote. The target start date for the role is January 1, 2026, and the application deadline is December 17, 202

• The position is categorized under a hardship level A, indicating a relatively low hardship environment. The role is full-time and involves significant collaboration with various stakeholders in the humanitarian sector.