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DEADLINE FOR APPLICATIONS
10 September 2024-23:59-GMT+01:00 Central European Time (Rome)

WFP celebrates and embraces diversity. It is committed to the principle of equal employment opportunity for all its employees and encourages qualified candidates to apply irrespective of race, colour, national origin, ethnic or social background, genetic information, gender, gender identity and/or expression, sexual orientation, religion or belief, HIV status or disability.

About WFP

The World Food Programme is the world’s largest humanitarian organization saving lives in emergencies and using food assistance to build a pathway to peace, stability and prosperity, for people recovering from conflict, disasters and the impact of climate change.

At WFP, people are at the heart of everything we do and the vision of the future WFP workforce is one of diverse, committed, skilled, and high performing teams, selected on merit, operating in a healthy and inclusive work environment, living WFP’s values (Integrity, Collaboration, Commitment, Humanity, and Inclusion) and working with partners to save and change the lives of those WFP serves.

Data Scientist Consultant to work with the project team on the development of the methodology for accessing the risk of dietary VMD and support the integration in HungerMapLIVE.

The Data Science team within the Early Warning and Forecasting Unit, in the Analysis Planning and Performance (APP) division, is a specialised 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. This proactive approach helps to mitigate the impact of potential crises on affected populations, improving resilience and ensuring food security.

The Early Warning and Forecasting Unit is collaborating with WFP’ Nutrition and Food Quality Service on a project to generate and increase access to modelled data on risk of dietary Vitamin and Mineral inadequacy at national and sub-national levels. This project will contribute towards the improvement of core Large-Scale Food Fortification (LSFF) program performance metrics, and in conjunction with data partners, will achieve consensus on approach, including the proxy indicator(s) for risk of dietary micronutrient risk. Specifically, the objective of the project is to develop a composite proxy-indicator for risk of inadequate dietary micronutrient intake and integrate it with in the HungerMapLIVE systems and related products.

Accountabilities/Responsibilities

The Consultant will be responsible for the following activities:

• Develop and test Machine Learning models for estimating risk of dietary micronutrient inadequacy at national and sub-national level, in collaboration with the rest of the Data Science team.
• Support ad-hoc data explorations and analysis for the project, by means of traditional statistical analysis as well as state-of-the-art data science methodologies.
• In collaboration with the software engineering team, support the design and the implementation of production-ready data pipelines for visualizing the data in the HungerMapLIVE.
• Support the writing of technical papers and reports to be submitted to peer-reviewed international journals.
• Participate in workshops, meetings and conferences to present the technical aspects of the project, within the organization and externally.
• 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 project methodology, including the code and methodology for the validation of the proxy indicators.
• Deploy machine learning models for the estimation of dietary micronutrient inadequacy in the required production environment.
• Support the visualization of the proxy indicators in the Hunger Map Live and related products.
• Participation in project meetings, scientific committee meetings and dissemination events.
• Presentations on the technical aspects of the project, as needed.

Education

QUALIFICATIONS & EXPERIENCE REQUIRED:

Master’s degree in engineering, computer science, physics, mathematics or similar.

Experience

From 1 to 5 years of professional experience in a data science-related position or field including PhD programmes and other academic positions.

Knowledge & Skills

• Python programming skills and experience with data science libraries (pandas, NumPy, scikit-learn, etc)
• Advanced knowledge of statistics and passion for machine learning with an understanding of algorithms
• Experience in git is a requirement
• Excellent communication and interpersonal skills, with the ability to work effectively and respectfully in a diverse and multicultural team environment
• Experience in designing and querying SQL databases is an asset
• Knowledge of survey methodologies is an asset
• Knowledge of food security and nutrition data is an asset
• Experience working with the humanitarian sector or in food security nutrition field is an asset.

Languages

Excellent spoken and written English

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REASONABLE ACCOMMODATION

WFP is dedicated to fostering diversity, equity, and inclusion. Our recruitment process is inclusively crafted to welcome candidates of all backgrounds, celebrating diversity and ensuring a respectful environment for all.

NO FEE DISCLAIMER

The United Nations does not charge any application, processing, training, interviewing, testing or other fee in connection with the application or recruitment process.

REMINDERS BEFORE YOU SUBMIT YOUR APPLICATION

• We strongly recommend that your profile is accurate, complete, and includes your employment records, academic qualifications, language skills and UN Grade (if applicable).
• Once your profile is completed, please apply, and submit your application.
• Please make sure you upload your professional CV in the English language
• Kindly note the only documents you will need to submit at this time are your CV and Cover Letter
• Only shortlisted candidates will be notified.

All employment decisions are made on the basis of organizational needs, job requirements, merit, and individual qualifications.