Junior HR Data Analyst Mr Price Group

3 weeks ago

Durban, South Africa Mr Price Group Full time

The purpose for the role is to conduct analyses and studies to support management in developing, recommending and administering effective compensation and benefits programmes in accordance with the organisation's reward strategy, philosophy & policies.

To compile, structure and analyse people data to make conclusions that help streamline all people related processes, how to store and process data, as well as to partner with the Divisional and Group People Managers by ensuring that they are updated on people issues, concerns and solutions by analysing relevant people information data and make recommendations based on insights and predictive analysis.
- Qualifications: Degree or Diploma in Human Resources Management or related field. Computer Science or Statistics and Finance qualification will be an added advantage.
- 3+ years as human resources generalist or other HR specialist fields
- 1 year in Data Analytics
- Advanced Excel and Data Analytics Skills.
- Basic understanding of Human Capital Management systems, Payroll systems and Microsoft Office Suite
- Experience with business intelligence tools such as Tableau & Power BI
- Added advantage payroll report writing (SQL)
- The ability to understand, interpret and communicate People insights and HR objectives in a clear and concise manner (ability to generate a story using data and visualisations).
- Added advantage retail exposure
- Continuous improvement mindset
- Stay current with industry trends and best practices in business intelligence, data analysis, and data visualization techniques- Responsibilities: Total Remuneration Benchmarking & Analysis:

- 1. Participates in total remuneration surveys, model salary increases, collect internal and external data to input into the development of salary structures & ensure a competitive posture in the relevant market(s). Studies and analyses compensation programs for local nationals and/or international personnel to provide input into managerial decisions about the organisation's compensation and benefit programmes.
- Remuneration Analytics:

- 1. Identifies remuneration data patterns & trends to report on/provide insights that enhance business decision making capability & planning. Identifies areas of improvement & recommends enhancements to policies to ensure organisational competitiveness to the market.
- Project Support:

- 1. Data analysis and support on projects. Scope dependent on project and tasks allocated within the project plan.
- Collaboration:

- 1. Effectively collaborate with Stakeholders and other functions/departments to drive and deliver on business objectives.
- Data Accuracy:

- 1. Monthly validation of data based on agreed principals.
- 1. Ensure the information stored in the database/people data warehouse is up-to-date and accessible for use.
- 2. Where necessary, make recommendations and implement continuous improvements to processes and data structures.
- Reporting:

- 1. Analyse data and report trends by performing statistical analysis on the data for better decision making.
- 2. Assist Group HR departments by providing data analysis according to specific requirements.
- 3. Contribute towards Group HR strategic reporting.
- 4. Engage with Business to develop meaningful remuneration dashboards and comparative ratio reports.
- 5. Ensure that at all times data, information and analysis emanating from the Reward team is timeous and accurate.
- Data Modelling & Visualisation:

- 1. Understanding source systems to model data with conformed measures in support of the HR Strategy.
- Support and Maintenance:

- 1. Make necessary enhancement to the reports and reporting techniques based on business requirements.
- 2. Prepare/update detailed documentation on processes, knowledge guides for the benefit of future HR Analysts
- 3.Updating and maintain existing dashboards
- Governance:

- 1. Ensure that data governance is adhered to at all times
- 2. Ensure that POPIA requirements are followed when using people data.
- 3. Implement Data Management processes and principles when handling data.

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