Sales Compensation Analyst (Financial Modeling & Planning)

S&P Global•London, CT

7d•$70,817 - $125,091

About The Position

The Sales Compensation Analyst is a quantitative specialist on S&P Global Market Intelligence’s globally connected Sales Compensation team. The role designs and runs financial simulation and scenario models to govern incentive spending across the global sales force. It forecasts commission accruals, stress-tests compensation structures, and produces predictive analytics to align compensation spend with divisional financial targets. The position assesses both potential outcomes before decisions and actual results afterward, ensuring plan design choices are grounded in evidence. The analyst builds dynamic forecasting models and automated reporting, develops plan effectiveness metrics, and creates reusable tools for modelling compensation scenarios. The role partners with Data Architecture teams to automate enterprise data ingestion and maintain the integrity, freshness, and accuracy of modelling inputs. It also translates quantitative findings into clear recommendations and executive presentations for Commercial and Finance leadership. The anticipated US base salary range is $70,817 to $125,091. Final base salary depends on geographic location, experience, skills, training, licenses, and certifications. The role is also eligible for an annual incentive plan and additional S&P Global benefits. Applicants must have indefinite authorization to work in the United States.

Requirements

At least 5 years of experience in financial modelling, quantitative compensation analysis, corporate FP&A, or incentive strategy within a multinational organisation.
Proven 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.
Demonstrated experience building sophisticated Power BI visualisation models using advanced DAX measures and star-schema architectures for executive-level reporting.
Demonstrated experience synthesising quantitative modelling outputs, including forecast results, stress-test findings, and attainment analyses, into clear, structured recommendations for senior Finance and Commercial executives.
Indefinite right to work in the United States.

Nice To Haves

Experience using corporate financial planning tools such as Adaptive Insights, Anaplan, or Workday Adaptive in a compensation or revenue planning context.
Experience applying Monte Carlo simulation or probabilistic modelling to sales compensation forecasting and tail-risk exposure quantification.
Experience constructing attainment distribution analyses and quota-cliff assessments to identify plan design distortions across global sales territories.
Experience analysing correlations between compensation expense ratios, including CAC and COC ratios, and product-line profitability or net new ACV in a B2B SaaS or subscription-based sales environment.
Experience building and maintaining version-controlled financial modelling repositories with longitudinal baseline data for multi-year compensation plan performance comparisons.
Experience partnering with Data Architecture or Data Engineering teams to design automated data ingestion pipelines from enterprise data warehouses into financial modelling workspaces.
Experience using Python SciPy, Statsmodels, or R for advanced statistical modelling, including regression analysis and distribution fitting, in a sales compensation or FP&A context.

Responsibilities

Build and execute dynamic financial forecasting models using Python (NumPy/Pandas) and advanced Excel/Power Query to simulate compensation expense under variable performance distributions, model global commission accruals, and estimate month-end payouts.
Cross-reference run-rate performance with historical seasonality trends to support FP&A alignment and payout estimates.
Perform multi-variable stress testing and sensitivity analyses of proposed compensation structures, including accelerator tiers, commission caps, milestone bonuses, and quota changes.
Forecast risk boundaries and tail-risk exposure, and construct statistical attainment distributions to identify plan distortions, windfall payouts, and quota cliffs across global sales territories.
Design and calculate plan effectiveness metrics, including analysis of compensation expense in relation to product-line profitability and net new ACV.
Evaluate the ROI and behavioural impact of non-standard incentive programs, including SPIFFs, strategic account bonuses, and multi-year contract multipliers.
Develop and maintain automated Power BI executive dashboards tracking global commission expense ratios, average realisation rates, CAC/COC ratios, and quota attainment curves.
Translate modelling outputs into clear executive presentations and briefing decks for Commercial and Finance leadership.
Build reusable script-based scenario calculators using Python, SQL, and Alteryx to simulate mid-year crediting and plan adjustments.
Maintain version-controlled mathematical repositories for longitudinal baseline comparisons across fiscal cycles.
Partner with Data Architecture teams to automate enterprise data warehouse ingestion into financial modelling workspaces and ensure pipeline integrity, data freshness, and modelling accuracy.