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.
As a Senior Data Analyst, Global Incentive Compensation Analytics, you 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.
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: Design and build a comprehensive framework to evaluate current payout rates against quota attainment, utilizing advanced data modeling to optimize commission multipliers and strategically align compensation structures across various roles and performance tiers.
Requirements:
- 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.
Benefits:
- Time off programs
- Medical, dental, vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program