- Location
- UK - London (London Wall), United Kingdom
- Type
- Full-time
- Source
- Workday
Description
Are you motivated by turning complex data into trusted, decision‑ready insights that directly impact how people are rewarded for their work?
Do you enjoy improving data processes and automation to make systems more accurate, scalable, and reliable?
About our Team
Our team supports the accuracy and integrity of sales and compensation data across the organisation. We work closely with Sales Operations, Finance, and technology partners to ensure data is reliable, well controlled, and ready for critical reporting and payout cycles. The team focuses on continuous improvement, strengthening data quality, increasing automation, and reducing risk through clear processes, collaboration, and shared accountability.
About the Role
This role focuses on building, validating, and maintaining high‑quality participant‑level data that underpins sales compensation outcomes. You will work across sales, finance, and technology partners to ensure data is accurate, auditable, and ready for payout cycles. The role plays a key part in improving automation, reducing manual effort, and strengthening stakeholder confidence in compensation data.
Responsibilities
- Ingest and consolidate large datasets from Sales Operations, Finance, and CRM systems
- Map transactions and performance metrics to sales participants
- Own data quality controls, reconciliation processes, and audit trails
- Ensure accurate attribution of revenue, quotas, credits, overlays, and splits
- Prepare validated datasets to support compensation payout cycles
- Investigate and resolve data discrepancies and support audits
- Build reporting to track data accuracy, readiness, trends, and risks
- Review end‑to‑end processes to identify inefficiencies and implement automation and standardisation
Requirements
- Strong experience working with large, complex datasets
- Advanced Excel skills for analysis, reconciliation, and validation
- Experience in analytics, sales compensation, or related data operations
- Ability to perform root‑cause analysis and solve data quality issues
- Clear communication skills to work with technical and non‑technical stakeholders
- Experience preparing data for financial or compensation processes
- Knowledge of SQL or Python
- Familiarity with compensation platforms, CRM systems, and data visualisation tools
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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