A4P+ Expert on Data Engineering and Machine Learning

Result of Service Supporting management and improvement of the A4P+ platform and data, the A4P+ Expert on Data Engineering and Machine Learning will deliver an expanded and optimized data pipeline architecture and improved data flow in support of organization requirements.The A4P+ Expert on Data Engineering and Machine Learning ensures compliance with data governance, protection and security needs.

Work Location New York / Remote

Expected duration Six months with possibility of extension.

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 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+ Expert on Data Engineering and Machine Learning will ensure effective data and platform management to enable and improve regular monitoring, analysis and reporting of the results of Action for Peacekeeping +. This includes building, managing and optimizing data pipelines and the existing architecture for A4P+ reporting to support the production of analytics, in compliance with data governance, protection, privacy and security requirements. As the platform requires updating following an examination of requirements for future reporting cycles, the Expert on data analytics and machine learning will advise upon changes required to the platform as well as roll-out capacity building initiatives to enable proper engagement with and utilization of the A4P+ reporting platform. The data engineers will closely support the work of the A4P+ Data Analyst.

Qualifications/special skills Academic Qualifications: Advanced university degree (Master’s degree or equivalent) in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field. A first-level university degree in combination with qualifying experience may be accepted in lieu of the advanced university degree.

Experience: Required: - A minimum of seven years of progressively responsible experience in data management, integration, modeling, optimization and other relevant areas. - Experience supporting cross-functional teams and collaborating with stakeholders in support of analytics initiatives is required. - Experience in Cloud services: Azure and Microsoft Power Apps is required. - Experience with database programming languages (SQL, etc.) is required. - Experience in designing data integration and pipeline architectures which must include ingesting data through different methods such as message queues, database connections, flat files, REST, or specific API’s, is required. - Experience with data visualizations - Experience with data modelling - Understanding of Artificial Intelligence algorithms such as deep learning, UNET

Desired: - Experience in Artificial Intelligence, particularly Machine Learning techniques for data mining and extraction of large amounts of data is desirable. - Experience working with self-service analytics applications like Microsoft PowerBI, Tableau, Qlik and others for data discovery is desirable. - Technical experience in: Languages: python, Jupyter Notebooks, R, Cloud services such as Amazon Web Services or other Geospatial DBs, libraries and data structures, Data visualization libraries, NoSQL database systems - Experience with geospatial data processing

Language: English and French are the working languages of the United Nations Secretariat. For the post advertised, fluency in English is required. Knowledge of any of the other UN official languages is desirable.

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 THE UNITED NATIONS DOES NOT CHARGE A FEE AT ANY STAGE OF THE RECRUITMENT PROCESS (APPLICATION, INTERVIEW MEETING, PROCESSING, OR TRAINING). THE UNITED NATIONS DOES NOT CONCERN ITSELF WITH INFORMATION ON APPLICANTS’ BANK ACCOUNTS.