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Sales Compensation Analyst, Financial Modeling – Planning
S&P Global. Design and run simulation and scenario models governing incentive spend across the global sales force .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in financial modeling and quantitative compensation analysis, utilizing advanced tools such as Python, SQL, and Power BI to deliver predictive analytics and optimize incentive strategies. Capable of synthesizing complex data into actionable insights for senior leadership in a multinational corporate environment.
Highest-signal resume keywords
Financial ModelingQuantitative Compensation AnalysisPython ProgrammingPower BI Data VisualizationSQL Querying
ATS Keywords
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Hard Skills
Financial ModelingQuantitative AnalysisDynamic Financial ForecastingMonte Carlo SimulationSensitivity AnalysisData ManipulationAdvanced ExcelDAX MeasuresScenario ModelingROI Evaluation
Soft Skills
CommunicationAnalytical ThinkingCollaborationPresentation SkillsProblem Solving
Tools & Technologies
PythonNumPyPandasPower BIAlteryxSQLAdaptive InsightsAnaplanWorkday AdaptiveSciPy
Industry Keywords
FP&AIncentive StrategyB2B SaaSSubscription-Based SalesData ArchitectureFinancial Modelling RepositoriesCompensation Expense RatiosQuota CliffsTail-Risk ExposurePlan Effectiveness Metrics
Tech Stack
Tools & technologiesNumpyPandasPythonSQL
About the role
Key responsibilities & impact- Design and run simulation and scenario models governing incentive spend across the global sales force
- Forecast commission accruals and deliver predictive analytics aligned with divisional financial targets
- Build and execute dynamic financial forecasting models using Python, NumPy, Pandas, advanced Excel, and Power Query
- Simulate sales compensation expense, model global commission accruals, and support FP&A alignment and month-end payout estimates
- Perform multi-variable stress-testing and sensitivity analyses on compensation structures
- Forecast risk boundaries and tail-risk exposure and identify plan distortions, windfall payouts, and quota cliffs
- Design and compute plan effectiveness metrics
- Analyse relationships between compensation expense, product line profitability, and net new ACV
- Evaluate ROI and behavioral impact of SPIFFs, strategic account bonuses, and multi-year contract multipliers
- Develop and maintain automated Power BI executive dashboards
- Translate quantitative modelling outputs into executive presentations and briefing decks for Commercial and Finance leadership
- Build reusable scenario calculators using Python, SQL, and Alteryx
- Enable rapid simulation of mid-year crediting and plan adjustments
- Maintain version-controlled mathematical repositories for longitudinal baseline comparisons
- Partner with Data Architecture teams to automate data ingestion from enterprise data warehouses
- Ensure pipeline integrity, data freshness, and modelling accuracy
Requirements
What you’ll need- 5+ years in financial modelling, quantitative compensation analysis, corporate FP&A, or incentive strategy within a multinational organisation
- Experience building nested logic models, dynamic array models, and Monte Carlo or multi-variable sensitivity simulations for large-scale compensation expense forecasting and risk quantification
- Hands-on experience using Python (Pandas/NumPy) or Alteryx for data manipulation and programmatic financial modelling
- Advanced SQL querying capability across large, multi-table datasets
- Experience building sophisticated Power BI data visualisation models using advanced DAX measures and star-schema architectures
- Experience synthesising complex quantitative modelling outputs into structured recommendations for senior Finance and Commercial executives
- Indefinite right to work in the United States
- Preferred: experience with Adaptive Insights, Anaplan, or Workday Adaptive
- Preferred: experience applying Monte Carlo simulation or probabilistic modelling techniques
- Preferred: experience constructing attainment distribution analyses and quota cliff assessments
- Preferred: experience analysing compensation expense ratios, product line profitability, or net new ACV in a B2B SaaS or subscription-based sales environment
- Preferred: experience maintaining version-controlled financial modelling repositories
- Preferred: experience partnering with Data Architecture or Data Engineering teams on automated data ingestion pipelines
- Preferred: experience using Python SciPy, Statsmodels, or R for advanced statistical modelling
Benefits
Comp & perks- Annual incentive plan
- Health care coverage
- Generous time off
- Continuous learning resources
- Competitive pay
- Retirement planning
- Continuing education program
- Company-matched student loan contribution
- Financial wellness programs
- Family benefits
- Retail discounts
- Referral incentive awards