The UN System Workplace Mental Health and Well-being Strategy (MHS) for 2024 and beyond was approved and launched in late 2023. The Strategy emphasizes a preventive and systemic approach to mental health. The Strategy presents a comprehensive framework aimed at:
Responsibilities:
Supporting staff experiencing mental health conditions.
To drive accountability and measure progress, the Strategy introduces clear success indicators for each of its three pillars.
A scorecard has been developed, featuring three indicators per pillar, and UN organizations are expected to report annually on their progress.
The first indicator under the Prevention pillar is Risk Assessment, which calls on organizations to evaluate psychosocial risks and implement practical mitigation plans to address identified concerns.
There is currently no standardized methodology across the UN system for assessing psychosocial risks, and existing data highlights the need for stronger preventive measures.
In response, the MHS Team is developing a unified psychosocial risk management model to ensure consistency in approach while allowing for contextual adaptation across the UN system.
This model reinforces the Strategy’s core principles of collaboration, shared responsibility, and system-wide Undertake data analysis and build the PSRM tool using advanced analytics, including machine learning, to identify risk patterns and predictive insights.
Establish a dynamic data visualization platform to present results interactively.
Pilot test the PSRM tool and prepare a technical paper documenting its methodology, validation, and application for internal and inter-agency reference.
Requirements:
Advanced university degree (PhD) in Occupational Health Psychology, Occupational Psychology, Organizational Psychology, or Management is required.
A minimum of 10 years of combined experience in psychosocial risk management, machine learning, and data analytics is required.
Experience of implementing multiagency psychosocial risk management projects with international organizations is required.
Experience in complex data analysis, including survey design, statistical interpretation, and data visualization/dashboard is required.
Experience in development of functional machine learning models for detecting risk patterns and generating predictive insights is required.
Experience in preparing technical documentation, methodological papers, or guidance materials for inter-agency stakeholders is required.
Experience drafting technical reports, policy briefs, and strategic documents for diverse audiences, including senior leadership, inter-agency stakeholders, and external partners is desirable.
Prior experience working with the UN system or other international organizations is desirable.
Active membership with a recognized professional body or relevant licensure/certification in Organizational Psychology, Occupational Psychology, or Management is desirable.
English and French are the working languages of the United Nations Secretariat.
Fluency in spoken and written English is required.
Knowledge of an additional official UN language is an advantage.
Arabic, Chinese, English, French, Russian and Spanish are the official languages of the United Nations Secretariat.
