At a Glance
- Tasks: Automate sales compensation processes and build data models for accuracy and compliance.
- Company: Join a globally connected team at S&P Global, known for integrity and innovation.
- Benefits: Enjoy competitive pay, health coverage, flexible time off, and continuous learning opportunities.
- Other info: Dynamic work environment with a commitment to equity and career growth.
- Why this job: Make a real impact by transforming complex compensation structures into automated solutions.
- Qualifications: 5+ years in sales compensation analytics with advanced SQL and Python skills.
The predicted salary is between 60750 - 74250 £ per year.
About the Role:
The Team
We are a high-accountability, globally connected Sales Compensation team that values disciplined execution, a strong sense of urgency, and end-to-end ownership. We expect our people to understand the full lifecycle of their work, anticipate downstream impacts, and communicate outcomes with exceptional clarity, whether supporting our broad population of 1,500+ plan participants or partnering with C-level executives. We value precision, responsiveness, sound judgment, collaboration, and people who take ownership through to resolution.
Responsibilities and Impact
This is a role for someone who sees a manual compensation process and immediately knows how to automate it. As the analytical and engineering engine behind S&P Global Market Intelligence's sales compensation function, you will convert complex commercial deal structures, multi-tier incentive plans, and governance controls into automated, audit-ready data models — building the infrastructure that makes accuracy scalable and compliance systematic.
- Translate and engineer complex commercial deal structures — including multi-year enterprise agreements, joint-production credit splits, co-selling models, and overlay allocations — into structured algorithmic logic and standardised business rules within the compensation calculation engine, eliminating manual offline adjustments and ensuring downstream calculation readiness.
- Model and simulate the financial impact of proposed changes to compensation plans and crediting rules — running Python and SQL scenario analyses on historical payout data and partnering with Revenue Operations and Legal/Deal Desk to evaluate non-standard transaction structures for data feasibility and commercial accuracy.
- Build and maintain automated reconciliation engines using Python, Alteryx, and SQL — cross-comparing ledger revenues, CRM bookings, and calculated commissionable revenue, and engineering variance detection models that automatically surface anomalies including revenue double-counting, territory misalignment, unassigned account credits, and clawback mismatches.
- Design and maintain governance control frameworks — building systematic tracking mechanisms for all manual adjustments with full origin, justification, and approval trails; directing comprehensive quarterly and annual SOX audit documentation; and running automated control test queries to demonstrate end-to-end calculation traceability.
- Architect and maintain enterprise Power BI reporting suites — developing advanced data models using DAX and Power Query M to visualise sales performance, attainment distributions, and compensation trends; building real-time Data Health and Anomaly monitoring dashboards; and presenting variance summaries, root cause analyses, and actionable insights directly to Finance and Commercial leadership.
- Standardise operations and advise stakeholders — converting fragmented legacy workflows into structured SOPs with clear SLAs; serving as the senior technical point of contact for Commercial and Finance stakeholders by translating complex data logic and calculation outcomes into plain-English explanations; and conducting technical peer reviews of queries, code updates, and configuration changes prior to production deployment.
What We Are Looking For
Basic Required Qualifications
- Experience: 5+ years in sales compensation analytics, financial modelling, or commercial data governance within a multinational organisation.
- SQL and Data Modelling: Advanced SQL proficiency for data modelling, validation, and complex multi-table reconciliation across ledger revenues, CRM systems, and compensation engines.
- Automation and Scripting: Hands-on experience using Python/Pandas or Alteryx to build automated reconciliation workflows, variance detection models, and data pipeline scripts.
- Power BI Development: Advanced Power BI expertise including data modelling, star schema design, complex DAX measures, and Power Query M transformations for enterprise-level reporting suites.
- Governance and SOX Controls: Proven experience operating within SOX-compliance frameworks — designing audit-ready controls, running automated control test queries, and producing end-to-end calculation traceability documentation.
Additional Preferred Qualifications
- Experience working within B2B SaaS or subscription-based sales compensation environments, including enterprise crediting rules, quota structures, and multi-tier incentive plan mechanics.
- Demonstrated experience presenting complex data logic, calculation methodologies, and compensation model outcomes to Finance and Commercial executive leadership in clear, non-technical language.
- Experience translating complex commercial contract mechanics — including multi-year enterprise agreements, joint-production credit splits, co-selling models, and overlay allocations — into structured algorithmic logic within enterprise compensation calculation engines.
- Experience partnering with Revenue Operations and Legal/Deal Desk to evaluate non-standard transaction structures for data feasibility and downstream compensation calculation readiness.
- Experience building real-time data health and anomaly monitoring dashboards that surface unmapped accounts, missing credit assignments, adjustment volume trends, and pipeline integrity issues.
- Experience designing and maintaining standardised adjustment protocols with systematic approval trail tracking for manual compensation overrides.
- Proven experience conducting technical peer reviews of SQL queries, automation scripts, and configuration changes prior to deployment in production compensation environments.
Right to Work Requirements
This role is limited to persons with indefinite right to work in the United States.
Equal Opportunity Employer
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law.
Sales Compensation Analyst (Commercial Modeling & Governance Automation) employer: Osttra
S&P Global is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a commitment to employee growth through continuous learning opportunities and a comprehensive benefits package, including health and wellness support, flexible downtime, and family-friendly perks, S&P Global empowers its employees to thrive both personally and professionally. Join a diverse team dedicated to advancing essential intelligence and making a meaningful impact in the global market.
StudySmarter Expert Advice🤫
We think this is how you could land Sales Compensation Analyst (Commercial Modeling & Governance Automation)
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We think you need these skills to ace Sales Compensation Analyst (Commercial Modeling & Governance Automation)
Some tips for your application 🫡
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How to prepare for a job interview at Osttra
✨Brush Up on Technical Skills
Make sure you're comfortable with key financial concepts, especially around forecasting, budgeting, and variance analysis. Sometimes, interviewers may throw in technical questions or case studies, so practicing these types of scenarios will help you shine!
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✨Connect with Company Goals
Familiarise yourself with Osttra's financial objectives and any recent developments. During the interview, try to weave your understanding of their business model and challenges into your answers—this shows your genuine interest and alignment with their goals!
