Sales Compensation Analyst, Financial Modeling – Planning

🔥 6 minutes ago

⛰️ Colorado, Connecticut, +7 more states – Remote

⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🌽 Illinois – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $70.8k - $125.1k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

💸 Financial Planning and Analysis (FP&A)

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S&P Global

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1860

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

S&P Global is a leading provider of market intelligence, ratings, analytics, and benchmark indices. The company offers comprehensive insights across various domains including finance, commodities, mobility, and sustainability. Renowned for its data-driven solutions, S&P Global assists organizations in navigating complex market trends, evaluating credit risk, and understanding the implications of artificial intelligence and energy transitions. Its diverse offerings, such as S&P Global Market Intelligence, S&P Global Ratings, and S&P Dow Jones Indices, provide critical data and analytics to businesses, government entities, and investors worldwide.

📋 Description

• 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 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, and quota cliffs • Design plan effectiveness metrics and analyze compensation expense, product 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 Python, SQL, and Alteryx scenario calculators for 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

• 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 • Right to work indefinitely in the United States • Preferred: experience with Adaptive Insights, Anaplan, or Workday Adaptive • Preferred: Monte Carlo simulation or probabilistic modelling techniques • Preferred: attainment distribution analyses and quota cliff assessments • Preferred: compensation expense, CAC/COC, profitability, and net new ACV analysis in B2B SaaS or subscription sales • Preferred: version-controlled financial modelling repositories • Preferred: automated data ingestion pipelines from enterprise data warehouses • Preferred: Python SciPy, Statsmodels, or R for advanced statistical modelling

🏖️ Benefits

• Annual incentive plan eligibility • Health care coverage • Generous time off • Continuous learning and career development resources • Retirement planning • Continuing education program with company-matched student loan contribution • Financial wellness programs • Family benefits and perks • Retail discounts • Referral incentive awards • Flexible fully remote work arrangement

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