This role will join our global shared service centre specialising in compensation for our colleagues around the World. This role will be responsible for handling administrative tasks as well as complex queries from our Centres of Expertise.
You will serve as the primary escalation point for all queries from Tier 1 People Services and will relieve our Centres of Expertise from administrative tasks, reporting and the management of complex queries.
What’s in it for you?
This is an opportunity to join a newly created team who will play a pivotal role in shaping and building our People Services function. The team has the autonomy to define the scope while embedding this new model. This Global team will deliver an efficient, colleague focused service, driving simplicity, new ways of working and standardisation.
Summary of your day-to-day?
- Complete Job evaluations for the business, which ensures fairness and consistency
- Support all colleagues and leaders compensation queries, managed through Service NOW ensuring effective ticket resolution
- Review and submit compensation pay data to external market leading pay surveys.
- Maintain and update manager supporting material contained in our online brochures on Page tiger.
- Responsible for all data cleansing and ensuring we have accurate data recorded in our HCM
- Supporting the pay review cycle by ensuring all data is accurate , carry out testing and completing a full data cleanse and regular audits. Test the compensation planning tools to ensure streamlined and efficient processes are in place and managers have a seamless journey when conducting year end Reward activities.
- Build and maintains strong and efficient working relationships with Management, Regional Reward Directors, HRIS, People Business Partners and corporate/business unit functions, etc.
- Proven experience in a reward team ideally focusing on compensation
- Strong understanding of market pay dynamics.
- Proficiency in English language, verbal and written.
- Intermediate Excel skills with the ability to draw meaningful and reliable conclusions from large, complex and sometimes incomplete datasets.
- Ability in basic statistics (mean, median, quartiles)