About Salesforce: We’re Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good– you’ve come to the right place.
Position Description: The Global Incentive Compensation (GIC) team at Salesforce is a global leader for sales compensation in the technology industry. We manage the sales compensation for all Salesforce, end-to-end - from designing the sales compensation plan to enable the company’s go-to-market strategy to administering the payment so that our sales teams get paid on time. We are currently hiring for an Senior Data Analyst, Global Incentive Compensation Analytics. This highly technical role will focus on generating deeper insights through sophisticated analysis and scientific modeling. You will support strategic compensation plan design decisions through data-driven recommendations, leveraging advanced statistical methods to assess the effectiveness of our existing programs. You will partner closely with stakeholders across the business to determine how best to align our plans with Salesforce’s strategic direction. The ideal candidate is comfortable working in a dynamic, data-driven environment, demonstrates natural curiosity, and is capable of building models that influence decision-makers.
Responsibilities:
Advanced Modeling & Simulation: Build and deploy scientific and predictive models using Python to simulate the financial and behavioral impacts of proposed compensation plan changes, providing analytics and data-backed business cases during the annual company GTM planning cycle.
Deep-Dive Analytics: Go beyond standard reporting to uncover hidden trends, performing sophisticated statistical analyses to evaluate the true effectiveness and ROI of various Incentive Compensation programs.
Data Pipeline & Automation: Extract, manipulate, and transform large datasets using advanced SQL and Python to automate deep insight generation, moving away from manual Excel-based processes.
Strategic Partnership: Serve as the dedicated technical analytics partner for aligned GTM organizations, translating complex scientific models into actionable business recommendations to evaluate the impact of compensation plan changes. Forecasting: Track commission costs by developing robust predictive algorithms that forecast future GTM performance and commission payouts.
Pay-for-Performance Framework: against quota attainment, utilizing advanced data modeling to optimize commission multipliers and strategically alignDesign and build a comprehensive framework to evaluate current payout rates
compensation structures across various roles and performance tiers.
Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related highly quantitative field.
Experience: 3+ years of related experience in Data Science, Advanced Analytics, or highly technical quantitative analysis.
Advanced Programming: Proficiency in Python (or R) for data manipulation, statistical analysis, and building scientific models.
SQL/Snowflake: Advanced proficiency in SQL/Snowflake, including complex query authoring, optimization, and troubleshooting.
Data Visualization: Proficiency in building sophisticated, automated dashboards in Tableau or a similar tool.
Analytical Problem Solving: Ability to independently address complex analytical requests: understand the ask, structure the data pipeline, perform advanced statistical analyses, validate assumptions, and output reliable scientific models.
Communication & Storytelling: Ability to synthesize complex data and scientific methodologies into simple, consumable deliverables with clear takeaways, influencing decision making and justifying recommendations across diverse audiences.
Industry Knowledge: A general understanding of how a SaaS GTM engine functions is preferred.
CRM: Knowledge of Salesforce products and/or CRM infrastructure preferred
