Data Scientist at World Food Programme (WFP)

BACKGROUND AND PURPOSE OF THE ASSIGNMENT:

• The Early Warning and Forecasting Unit is committed to addressing the pervasive challenge of food insecurity through innovative and data-driven approaches. To this end, we seek to leverage advanced analytical capabilities, including AI and data science techniques, to better understand, model, and forecast food insecurity and its drivers. The Data Science team within the Early Warning and Forecasting Unit in the Vulnerability Assessment and Mapping service, is a specialized team dedicated to addressing the challenge of modelling and forecasting food insecurity and its drivers through the innovative application of machine learning and data science techniques By leveraging large heterogenous datasets and
• advanced algorithms, the team can identify patterns and trends that are not immediately apparent and predict the impact of impending natural and human generated hazards, enabling timely interventions and anticipatory actions in vulnerable areas. The work is crucial in facilitating data-driven decision-making for governments and humanitarian organizations, allowing proactive strategies in combating food crises and their underlying causes. This proactive approach helps to mitigate the impact of potential crises on affected populations, improving resilience and ensuring food security.
• This project harnesses expertise in artificial intelligence and product innovation alongside WFP's operational insights and localized data to generate early warning signals that facilitate proactive interventions. The system integrates real-time data, satellite imagery, news data streams to enhance response capabilities and improve the efficiency and effectiveness of efforts to prevent food crises in vulnerable communities.
• The Data Scientist will be primarily responsible for designing and developing a robust early warning model for food which encompasses creating advanced AI solutions to analyse trends, forecast potential crises, and generate early warning. A crucial aspect of this role is the constant integration of feedback from domain experts within the WFP Country Offices, ensuring the system's relevance, accuracy, and usability for local operational planning and decision-making. Furthermore, the Data Scientist will be tasked with expanding and integrating datasets, adhering to established guidelines, to enrich the early warning system's analytical capabilities and provide comprehensive insights. All models developed will be in production-ready code to ensure smooth maintenance and deployment within the County Offices analytical frameworks.

ACCOUNTABILITIES/RESPONSIBILITIES:
The Consultant will be responsible for the following activities:

• Develop state of the art Machine Learning end to end inference pipelines, from automated ingestion of data sources to the production of early warnings.
• Research, design and implement models for estimating food insecurity and produce early warning of impending crises.
• Lead the interactions with HQ and Cos on the development of the early warning platform by integrating feedback from national stakeholders.
• Coordinate with technical leads in the design of data platforms to privately and publicly share the early warnings.
• Measure and monitor the impact of the early warning platform in the Country Offices daily tasks.
• Ensure adherence to WFP policies regarding data, including data privacy, security, management, and code documentation.
• Participate in field missions to WFP country offices as required.
• Perform other tasks as required.

DELIVERABLES AT THE END OF THE CONTRACT:

• Technical inputs to the development of Early Warning System, including the code and methodology for generation of the signals.
• Deployment of models in a production environment
• Maintenance of the code base following industry's best practice
• Impact evaluation document of early warning platform.
• Participation in project meetings, scientific committee meetings and dissemination events.
• Presentations on the technical aspects of the project, as needed.

QUALIFICATIONS & EXPERIENCE REQUIRED:

Education:

• Master's degree in a quantitative field

Experience:

At least 5 years of professional experience in an analytical role

Knowledge & Skills:

• Python programming skills and experience with data science libraries
• Advanced knowledge of machine learning
• Experience in querying SQL databases is required
• Experience in GIT is an asset
• Experience in forecasting methodologies is an asset
• Knowledge of survey methodologies
• Excellent communication and interpersonal skills, with the ability to
• work effectively and respectfully in a diverse and multicultural team
• environment

Languages:

• Excellent spoken and written English. French or Arabic is an asset.