UK remote
Sales Compensation Analyst (Commercial Modeling & Governance Automation)
About this role
About the Role: Grade Level (for internal use): 10 Sales Compensation Analyst – Commercial Modelling & Governance Automation The Team We are a high-accountability, globally connected Sales Compensation team that values disciplined execution, a strong sense of urgency, and end-to-end ownership. We expect our people to understand the full lifecycle of their work, anticipate downstream impacts, and communicate outcomes with exceptional clarity, whether supporting our broad population of 1,500+ plan participants or partnering with C-level executives.
We value precision, responsiveness, sound judgment, collaboration, and people who take ownership through to resolution. Responsibilities and Impact This is a role for someone who sees a manual compensation process and immediately knows how to automate it. As the analytical and engineering engine behind S&P Global Market Intelligence's sales compensation function, you will convert complex commercial deal structures, multi-tier incentive plans, and governance controls into automated, audit-ready data models — building the infrastructure that makes accuracy scalable and compliance systematic.
If you combine deep technical fluency in SQL, Python, and Power BI with a genuine understanding of how enterprise compensation works, this role offers the scope, the complexity, and the leadership exposure to match. Translate and engineer complex commercial deal structures — including multi-year enterprise agreements, joint-production credit splits, co-selling models, and overlay allocations — into structured algorithmic logic and standardised business rules within the compensation calculation engine, eliminating manual offline adjustments and ensuring downstream calculation readiness.
Model and simulate the financial impact of proposed changes to compensation plans and crediting rules — running Python and SQL scenario analyses on historical payout data and partnering with Revenue Operations and Legal/Deal Desk to evaluate non-standard transaction structures for data feasibility and commercial accuracy. Build and maintain automated reconciliation engines using Python, Alteryx, and SQL — cross-comparing ledger revenues, CRM bookings, and calculated commissionable revenue, and engineering variance detection models that automatically surface anomalies including revenue double-counting, territory misalignment, unassigned account credits, and clawback mismatches.