Job Description

Deadline for Applications

December 17, 2025

Hardship Level (not applicable for home-based)

A (least hardship)

Family Type (not applicable for home-based)

Family

Staff Member / Affiliate Type

UNOPS IICA1

Target Start Date

2026-01-01

Terms of Reference

1. General Background

Project 21 (P21) is a UNHCR and DRC co-facilitated regional protection monitoring initiative designed to strengthen evidence-based protection responses across West and Central Africa. The inter-agency initiative mobilizes humanitarian partners to collect and analyze protection data in displacement-affected contexts, Through standardized tools and collaborative data collection. P21 represents a strategic initiative that relies heavily on evidence-based decision-making to achieve its objectives. The complexity of humanitarian and development challenges addressed under P21 requires accurate, timely, and actionable insights drawn from large and diverse datasets. A data scientist plays a critical role in this process by transforming raw data into meaningful intelligence through advanced analytics, predictive modeling, and visualization. Their expertise ensures that decision-makers can anticipate trends, allocate resources efficiently, and monitor progress against key indicators. Without robust data science support, P21 risks operating on fragmented information, limiting its ability to respond effectively and optimize impact.

Furthermore, the growing insecurity and restricted humanitarian access across the Central Sahel region pose major challenges to protection data collection and response planning. Traditional methods are increasingly impractical due to conflict, displacement, and infrastructure disruptions. To address the lack of reliable data in inaccessible areas, Project 21 secured funding to build a predictive machine learning model that integrates diverse datasets—from conflict and displacement to food insecurity and environmental hazards—to infer protection risks and humanitarian needs. This innovative approach aims to enable continuous monitoring and targeted protection interventions, even in areas where physical access is impossible, thereby strengthening humanitarian response across the Sahel and beyond

2. Purpose and Scope of Assignment
The Data Scientist will dedicate 50% of his/her time to support the building of the predictive model in close collaboration with the Project Lead and team, UNHCR data scientist, DIMA team, the project’s associate information management officer, the Protection Unit, and the Protection Cluster in Niger.
In parallel, the consultant expected to spend the remaining 50% of the time to provide support to Project 21’s mainstream activities, on which he/she will work in collaboration with the P21 and DIMA regional teams
This dual role ensures that both the innovation and core protection monitoring components are effectively coordinated and contribute to evidence-based protection programming.
The consultant will work under the supervision of the project 21 coordinator

1) Innovation project;
The Data Scientist will lead the design, development, and deployment of the predictive analytics model, ensuring technical robustness, ethical compliance, and operational relevance. This includes designing statistical methodologies, implementing machine learning algorithms, constructing composite indices, and ensuring robust data imputation strategies.

Key Responsibilities
a. Data Acquisition and Integration: Collect, clean, and harmonize datasets from ACLED, WFP, WorldPop, satellite imagery, UNHCR internal data etc ; ensure data quality and compliance with UNHCR’s data protection standards. Collect, clean, and harmonize datasets from multiple sources (e.g., ACLED, WFP, WorldPop, satellite imagery, UNHCR). Apply spatial and temporal aggregation to align different granularities, ensure preprocessing and standardization, and implement validation and quality assurance throughout the data pipeline.

b. Model Development:. Design and implement predictive models using diverse machine learning. Train, validate, and optimize models with historical and real-time data, ensuring transparency, interpretability, and alignment with humanitarian principles. Maintain reproducible workflows and document all decisions, assumptions, and methodologies.
c. Construct composite indices and vulnerability indicators using established statistical frameworks; develop and implement algorithms for data imputation and gap-filling to address missing data in conflict-affected and hard-to-reach areas.

d. Pilot Testing and Evaluation: Deploy the model in the Tillabéri region for pilot testing; compare predictions with available field data and refine the model based on feedback.Geospatial Analysis and Visualization : Work closely with Information Management, Protection, and DIMA teams to map protection risks and humanitarian needs by developing user-friendly visualizations like dynamic risk and heat maps, and interactive dashboards for diverse audiences.
e. Capacity Building ;conduct training sessions for UNHCR staff and partners,Develop user guides and SOPs for model deployment and maintenance and training materials
f. Ethical and Risk Management: Implement safeguards to prevent misuse of predictive outputs; ensure transparency and explainability of the model.

2. Project 21 mainstream activities

- Apply data science techniques to monitor protection risks and trends in forced displacement and statelessness.
- Identify patterns in population behavior, vulnerabilities, and protection needs using advanced analytics.
- Develop predictive models to anticipate protection risks, displacement flows, and emerging vulnerabilities.
- Use machine learning to inform proactive protection interventions.
- Develop indicators and KPIs to assess the effectiveness of protection strategies.
- Apply statistical methods to evaluate the impact of UNHCR protection programmes.
- Automate routine protection data processing and reporting tasks.

3. Monitoring and Progress Controls

The Data scientist will: -
- define objectives with the supervisor at the beginning of the contract.
- produce weekly brief and monthly status reports which will form part of the end of year report.
- Deliver the key outputs below:
a. Harmonized dataset and metadata documentation
b. Predictive model with performance metrics (accuracy ≥70%)
c. Pilot evaluation report with recommendations for scale-up
d. Training materials and user guides for field teams.

4. Qualifications and Experience

For this specific role, the ideal candidate will have the following qualifications:

- Demonstrated notion in survey methodology including survey sampling, design of questionnaires and conduction of continuous and non-continuous surveys in conflict zones, humanitarian emergencies, and development contexts.
- Strong statistical knowledge and profound understanding of statistical concepts and methods, facilitating use of appropriate analysis techniques to ensure accurate data interpretation.
- Experience with data sharing, data anonymization, statistical disclosure control, data management, and data analysis.
- Experience with data visualization tools such as D3.js, Power BI, Dash, Shiny, or Tableau.
- Prior experience working on protection/protection monitoring and socio-economic data or the cluster or any coordination mechanisms would be an added advantage.
- Experience working in/knowledge of the west and Central Africa context and data collection dynamics and challenges in conflict and forced displacement situations.
- Capacity building skills and ability to provide technical support to P21 data related functions within UNHCR and implementing partners at regional and country level.

Some of the more specific tasks will include:

- Develop an agile code infrastructure to pipe, monitor, explore and exploit real-time survey data relating to forced displacement and statelessness situations;
- Advance analytical techniques and data quality assurance approaches in UNHCR, aligning them to statistical standards and analytical best practices.
- Support the development and enhancement of UNHCR data systems interoperability and systematic adoption by providing advice on data science techniques.
- Contribute to the delivery of high-profile analytical products, in consultation with the relevant operational teams, including field operations.
- Facilitate open access to anonymized forced displacement data while addressing protection and privacy concerns over microdata managed by UNHCR.
- Provide consultation and guidance to non-technical audiences and develop and implement guidance on integrating advanced data and analysis in routine decision-making processes.

a. Education:
- Advanced university degree (master’s or PhD) in Data Science, Statistics, Computer Science, Applied Mathematics, Computational Social Sciences, or related quantitative field

b. Work Experience:
- For P2/NOB - 3 years relevant experience with Undergraduate degree; or 2 years relevant experience with Graduate degree; or 1 year relevant experience with Doctorate degree.
c. Key Competencies:
(Technical knowledge, skills, managerial competencies or other personal competencies relevant to the performance of the assignment. Clearly distinguish between required and desired competencies)

Essential:
Strong quantitative background in statistics, economics, mathematical or computer science modelling or similar; experience in data collection, management, cleaning, processing, and applied analysis using statistical software or computer/programming languages such as Python, Stata, SAS, R, SPSS, MATLAB, SQL etc. Demonstrated experience in ensuring the operational relevance of analytical and/or research work. Solid understanding of forced displacement-related issues. Drive, proven sense of initiative, results orientation, flexibility, leadership qualities, as well as effective teamwork skills. Experience working with Big Data and/or Statistical Learning methods. Experience writing technical reports. Demonstrated experience presenting work to both technical and non-technical audiences. Willingness to experiment in data innovation and big data and push the boundaries in applying technical skills for development and humanitarian action. Ability to work flexibly, creatively and to multitask as the need arises. A high degree of self-motivation, positive attitude and drive.

Desirable:
Experience in process re-engineering (process redesign, process transformation, or change management). Experience with data sharing, data anonymization, statistical disclosure control, data management, and data analysis. Experience with data visualization tools such as D3.js, Power BI and Tableau. Experience with UNHCR's corporate applications and operational data. Demonstrated understanding of civil registration and other national population registration systems. Knowledge of UNHCR and interagency policies, standards, programmes and operations.