Wiser Educação
HR Analytics Manager
Skills
19 days ago
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Important information
Contract type:
Part time
Location:
United Arab Emirates
Work mode:
Remote
Published on:
6 October 2026
What they need
Role Description The HR Analytics Manager is a part-time, remote role responsible for leading data-driven initiatives within the Human Resources function. This role involves designing and maintaining HR and people analytics dashboards, analyzing workforce data, and generating insights to support talent, engagement, and organizational effectiveness strategies. The HR Analytics Manager will partner with HR and business stakeholders to define key metrics, produce reports, and recommend actions based on trends in employee performance, retention, recruitment, and development. Day-to-day tasks include data collection and validation, building and updating analytics models, managing HR analytics projects, and communicating findings in a clear, accessible way to support strategic decision making.
Qualifications
- Candidates should possess strong HR Analytics and People Analytics skills to design, implement, and interpret workforce metrics.
- Candidates should possess robust Analytical Skills to work with complex datasets, perform quantitative analysis, and derive actionable insights.
- Candidates should possess Human Resources (HR) knowledge to contextualize data within HR processes such as recruitment, performance management, and employee engagement.
- Candidates should possess Project Management skills to plan, execute, and monitor HR analytics initiatives and deliverables.
- Relevant experience with data visualization tools (e.g., Power BI, Tableau, or similar) and HRIS or HR data systems is beneficial.
- Strong communication skills, including the ability to present findings to both technical and non-technical stakeholders, are required.
- A bachelor’s degree in Human Resources, Business, Statistics, Data Science, or a related field, or equivalent practical experience, is preferred.
- Ability to work independently in a remote setting, manage multiple priorities, and maintain high standards of data accuracy and confidentiality is essential.
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