Overview
The incumbent will act as the lead analyst and focal point for AI-driven food security forecasting, and RAM Ecosystem and geospatial analysis. The position operates with a high degree of independence and coordinates with various teams.
Key Responsibilities
- Lead the technical execution of the AI/ML food security forecasting pipeline, including development and validation of models.
- Develop and integrate the NLP module for processing qualitative food security narratives.
- Manage multi-sensor satellite data integration and ensure data pipeline quality.
- Design and deploy the Tableau dashboard with REST API for automated data ingestion and visualization.
- Maintain and extend data-sharing agreements and technical partnerships.
- Coordinate HQ VAM Data Scientist peer review and respond to comments.
- Prepare and submit project reporting and milestone updates to HQ VAM.
- Lead government capacity building on system use and deliver the full handover package.
- Coordinate the RAM Ecosystems team workplan by prioritizing deliverables and managing requests.
- Ensure timely delivery of high-quality analytical outputs, including digitalization of data collection tools.
- Oversee the maintenance, development and continuous update of existing Tableau dashboards.
- Ensure the timely production and quality assurance of thematic and operational maps.
- Maintain and ensure compliance with corporate platforms and data management systems.
- Provide direct supervision, mentorship, and technical guidance to Data Analysts.
- Represent the RAM Ecosystems unit in CO coordination meetings.
- Lead and coordinate RAM Ecosystems & Analytics data governance processes.
- Ensure that data collection, processing, sharing, and analytics activities comply with WFP standards.
- Support the implementation of WFP’s data governance architecture.
- Provide technical guidance on privacy-by-design approaches.
Required Experience
- Minimum 5 years of progressively responsible professional experience in Data Science, Information Management or analytics in a humanitarian or development context, of which at least 3 years in operational food security, VAM or climate risk analysis.
- Demonstrated proficiency in Python (Pandas, NumPy, scikit-learn, PyTorch or TensorFlow).
- Experience building AI/ML pipelines including ensemble models (CNN, LSTM, XGBoost).
- Working experience with NLP (BERT or equivalent transformer models).
- Database proficiency in SQL; familiarity with ETL pipelines and data engineering workflows.
- Production-grade dashboarding in Tableau including REST API integration and automated refresh.
- Working knowledge of Power BI.
- Experience producing technical reports and documentation for operational and management audiences.
- Working knowledge of ArcGIS Online (Operational Dashboards, web maps, web applications).
- Ability to produce thematic and operational maps for programme and field support.
- Familiarity with WFP corporate platforms including HungerMap, PRISM and GeoNode is an asset.
- Working knowledge of WFP corporate data systems (SCOPE, KoBo / MoDa, SugarCRM, DataLib) and data protection standards (DPIA, WFP Guide for Personal Data Protection and Privacy).
- WFP country office experience is desirable.
Qualifications
- Advanced University degree (Master's or equivalent) in Data Science, Computer Science, Applied Statistics, Information Management or a quantitative field relevant to food security analysis.
- A first degree with at least 7 additional years of relevant experience may be considered.
