Sales Compensation Analyst (Financial Modeling & Planning)

S&P Global•Hightstown, NJ

7d•Remote

About The Position

The Sales Compensation Analyst is a quantitative specialist on S&P Global Market Intelligence’s global Sales Compensation team. The role designs and runs financial simulation and scenario models to support incentive-spend planning across the global sales force. It forecasts commission accruals, stress-tests compensation plan structures, and provides predictive analytics to help align compensation spending with divisional financial targets. The work includes modelling potential outcomes before decisions and evaluating actual results afterward, ensuring plan decisions are grounded in evidence. The analyst builds forecasting models and scenario calculators, assesses plan effectiveness and risk, and develops automated executive dashboards and presentations for Commercial and Finance leadership. The role also partners with Data Architecture teams to automate data ingestion and maintain the integrity, freshness, and accuracy of modelling inputs. The team supports more than 1,500 plan participants and partners with stakeholders including C-level executives.

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 and dynamic-array models, as well as Monte Carlo or multi-variable sensitivity simulations for compensation expense forecasting and risk quantification.
Hands-on experience using Python (Pandas/NumPy) or Alteryx for data manipulation and programmatic financial modelling, together with advanced SQL querying across large, multi-table datasets.
Demonstrated experience building sophisticated Power BI data visualisation models using advanced DAX measures and star-schema architectures for executive reporting.
Demonstrated ability to synthesise complex modelling outputs, including forecast results, stress-test findings, and attainment analyses, into structured recommendations for senior Finance and Commercial executives.
Indefinite right to work in the United States.

Nice To Haves

Experience with 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 quantification.
Experience constructing attainment distribution analyses and quota-cliff assessments to identify plan design distortions across global sales territories.
Experience analysing relationships 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 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, 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, including accelerator tiers, commission caps, milestone bonuses, and quota changes.
Construct statistical attainment distributions to identify plan distortions, windfall payouts, quota cliffs, and tail-risk exposure across global sales territories.
Design and compute plan effectiveness metrics, analysing relationships between compensation expense, product-line profitability, and net new ACV; evaluate the ROI and behavioural impact of non-standard incentive programs.
Develop and maintain automated Power BI executive dashboards tracking commission expense ratios, 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 data ingestion from enterprise data warehouses into financial modelling workspaces and ensure pipeline integrity, data freshness, and modelling accuracy.