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Systems Specialist Head Office - South Africa

Daybreak Foods Ltd

DAYBREAK FOODS requires the services of a suitably qualified, well-motivated and results driven candidate that will be focused on improving HR processes and organizational efficiency using data-driven insights. Their role involves analysing HR data to identify trends and enhance systems, ensuring operational improvements. They also maintain data accuracy and integrity, which supports reliable decision-making, compliance, and strategic planning Utilize data analytics to identify trends, patterns, and opportunities for process improvement within the HR department. Develop and maintain HR metrics, dashboards, and reports to provide valuable insights to key stakeholders. Collaborate with cross-functional teams to implement data-driven solutions that support HR initiatives and business objectives. Conduct in-depth analysis on employee data, performance metrics, recruitment, retention, and training effectiveness. Ensure data integrity and accuracy within HR systems, identifying discrepancies and recommending corrective actions. Stay abreast of industry best practices and emerging trends in HR analytics to drive continuous improvement. Communicate findings and recommendations to senior management in a clear and concise manner. Participate in the development and implementation of HR technology projects to enhance efficiency and effectiveness. Bachelor's degree in Human resources, Business Administration, Data Science, or a related field. At least 5 years of extensive experience with HR Systems (e.g. HRIS, ATS, BI tools) and data management tools Proven proficiency with SAGE 300 Payroll/HR, Employee Self-Service (ESS), and Time & Attendance systems, with a minimum of 5 years of experience. Demonstrated expertise in project management with a focus on implementing data-driven HR solutions, requiring at least 5 years of experience. Certifications in HR analytics and Data management are advantageous, with a minimum of 5 years of relevant experience. Proficiency in statistical analysis and predictive modelling. Apply Now
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