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A4P+ AI and Machine Learning Expert

New York City

  • Organization: UN - United Nations
  • Location: New York City
  • Grade: Level not specified - Level not specified
  • Occupational Groups:
    • Education, Learning and Training
    • Information Technology and Computer Science
    • Conflict prevention
    • Peace and Development
    • Innovations for Sustainable Development
  • Closing Date: 2022-12-01

Result of Service

The result of the services provided by the A4P+ IC on Artificial Intelligence (AI) and Machine Learning include:

• A data model for the use in A4P+ analysis;
• Services to the A4P+ team to enable transition and build capacity; and
• Documentation of the work undertaken to enable transition of the work to the Organization.

Work Location


Expected duration

6 months

Duties and Responsibilities

The Secretary-General launched Action for Peacekeeping on 28 May 2018 and its Declaration of Shared Commitments, endorsed by 154 Member States, remains a roadmap for our collective efforts to strengthen peacekeeping. Three years on, the moment arrived to take stock, closely assess achievements, challenges, gaps and accordingly, determine what key priorities need to be addressed in the coming years. On 29 March 2021, the Secretary-General introduced Action for Peacekeeping + (A4P+), a set of seven discrete priorities designed to accelerate the ability of the UN Secretariat to fulfill its commitments within the Declaration. Complementing the SG's Data Strategy, A4P+ calls for UN Peacekeeping to accelerate our move toward "innovative, data-driven and tech-enabled peacekeeping." As UN Peacekeeping implements A4P+, continuing to measure, verify and report on progress and the impact of efforts to strengthen peacekeeping effectiveness remains critical.

Building on the notable progress evaluating the performance of UN peacekeeping, the Office of the Under-Secretary-General for Peace Operations (OUSG DPO) has developed a new platform and monitoring framework to systematically monitor, evaluate and report on peacekeeping performance, as outlined in the A4P+ framework, using quantitative and qualitative data. It builds off of and connects to existing tools, including the Situational Awareness Capabilities (Unite Aware) and the Comprehensive Planning and Performance Assessment System (CPAS).

The A4P+ IC on Artificial Intelligence (AI) and Machine Learning will report to the A4P+ Data Engineer in OUSG DPO, providing support and advice to the A4P+ Data Engineer to apply machine learning and statistical techniques, particularly on natural language processing and text analytics.

Within delegated authority, the IC on AI and Machine Learning will be responsible for the following duties:

• Guide the data analyst and data engineer to provide exploratory data analysis on both vector and raster datasets.
• Support the process to create, train, test, and validate structured and unstructured datasets for AI model development.
• Advise on and assist in conceptualizing and implementing various AI models at scale.
• Build the Machine Learning and AI models for predicting various connectivity variables.
• Assist in building and maintaining deployment pipelines for the AI models, using the Microsoft 365’s tools or other available development tools.
• Write a report on the analysis and recommendation on the business improvements needed for the Department of Peace Operation.
• Assess the comprehensiveness, validity, and accuracy of new data sources and data gathering techniques; explore sources to determine their effectiveness and accuracy for use and assess their suitability for actionable output.
• Develop custom data models and algorithms to apply to peacekeeping A4P+ data sets.
• Develop and maintain comprehensive and well-structured documentation of algorithms, models, and code.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Liaise with technology stakeholders to access infrastructure, software, and services needed to develop and deploy data science products.
• Develop products, tools, and processes to periodically validate the effectiveness of data science products and their expected and observed benefits; iteratively improve models based on findings (test model quality) and undertake regular model maintenance.
• Design and build predictive data science products, such as visualizations, models or Artificial Intelligence/Machine Learning (AI/ML) algorithms for initial simulations or prototypes, and subsequent ingestion into mainstream software applications.
• Manage and maintain existing production code (e.g. Azure, AWS), progress and optimize existing code for adaption to other thematic areas and evolving project objectives.
• Develop predictive modelling to increase and optimize AI/ML outcomes.
• Develop methodological guidelines for dissemination purposes on selected topics including on reproducibility, deduplication, and use of social media; maintenance and updating of data harvesting and ML model technical documentation.
• Create a central repository of sources used for ‘web scraping’ activities used to develop datasets.

Qualifications/special skills

- Applicants to positions at this level who have an advanced university degree in a relevant field of study are not required to have professional work experience. For applicants who have a first level university degree, two additional years of qualifying work experience is required.

- Experience with data visualizations
- Experience with data modelling
- Understanding of AI algorithms such as deep learning, UNET
- Experience with geospatial data processing
- Technical experience in:
o Languages: Python, Jupyter Notebooks, R,
o Cloud services: Azure, AWS, etc
o Geospatial DBs, libraries and data structures
o Data visualization libraries, data visualization tools (Power BI, Tableau, Qlik)
o Sql and NoSQL database systems
o Desirable: Deployment tools (Streamlit, Dash, Heroku, API frameworks)
- Knowledge of NLP models is desirable


Fluency in one of the working languages of the UN Secretariat, English or French, (both oral and written) is required; knowledge of the other is desirable. Knowledge of another UN official language is an advantage.

Additional Information

The United Nations Secretariat is committed to achieving 50/50 gender balance and geographical diversity in its staff. Female candidates are strongly encouraged to apply for this position.

Candidates should list all work experience and diplomas in the relevant part of the application. Work experience and diplomas only mentioned in the cover letter will not be considered for screening purposes. Statements must include concrete start and end dates, detailed description of tasks and achievements and whether the experience was obtained in full-time or part-time. Candidates should note that eligibility and fees will be decided based on their submitted application only. There is no option to revise an application after submission.

No Fee


We do our best to provide you the most accurate info, but closing dates may be wrong on our site. Please check on the recruiting organization's page for the exact info. Candidates are responsible for complying with deadlines and are encouraged to submit applications well ahead.
Before applying, please make sure that you have read the requirements for the position and that you qualify.
Applications from non-qualifying applicants will most likely be discarded by the recruiting manager.

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