Remote Sales Compensation Modeling Analyst

S&P Global; Greater London; Remote; GBP 53,000 - 94,000; Full time

Benefits offered by this job

Health care

Flexible time off

Learning & development

Retirement plan

Family perks

Job summary

S&P Global's Sales Compensation team seeks a seasoned Analytics professional to design and operate the financial engine for global sales compensation planning. You will model incentive spend, stress-test plans, and forecast accruals to align with divisional targets.

You will build dashboards in Power BI, develop Python/SQL based calculators, and partner with FP&A and Commercial leadership to translate complex data into strategic recommendations.

Qualifications

• 5+ years in financial modelling, FP&A, or incentive strategy within a multinational.
• Advanced modelling with nested logic, dynamic arrays, Monte Carlo or multi-variable simulations.
• Proficiency in Python (Pandas/NumPy) or Alteryx and SQL.
• Power BI development with DAX in executive reporting.
• Strong communication of complex analyses to senior leadership.

Responsibilities

• Build and run dynamic forecasting models using Python and Excel, simulating compensation expense and accruals.
• Perform stress-testing and sensitivity analyses on compensation structures to forecast risk.
• Design metrics linking compensation to profitability and ACV impact.
• Develop Power BI dashboards tracking commission expense ratios and quota attainment.
• Create script-based scenario calculators in Python/SQL/Alteryx for quick mid-year adjustments.
• Collaborate with Data Architecture to automate data ingestion and ensure data quality.

Skills

Financial modelling

Tools

Python (Pandas/NumPy)

SQL

Power BI

Alteryx

Job description

S&P Global's Sales Compensation team seeks a seasoned Analytics professional to design and operate the financial engine for global sales compensation planning. You will model incentive spend, stress-test plans, and forecast accruals to align with divisional targets.

You will build dashboards in Power BI, develop Python/SQL based calculators, and partner with FP&A and Commercial leadership to translate complex data into strategic recommendations.