Data Scientist, Revenue Analytics

Responsibilities

• Develop statistical models and analytical frameworks that measure the impact of marketing, sales, and customer success initiatives on pipeline, bookings, ARR, renewal, and expansion

• Analyze the effectiveness of paid media investments, including channel performance, return on advertising spend (ROAS), customer acquisition cost (CAC), and marketing ROI

• Build predictive models to identify drivers of customer acquisition, free trial conversion, customer retention, expansion, and churn

• Design and evaluate experiments to measure incremental business impact and inform strategic investment decisions

• Partner with cross-functional stakeholders to define success metrics and build measurement strategies across the customer lifecycle

• Develop forecasting models to support revenue planning and investment decisions

• Communicate analytical findings to senior leaders through clear storytelling and data visualization, translating complex analyses into business recommendations

• Continuously improve data quality, measurement methodologies, and analytical best practices across the organization

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Data Science, or a related quantitative field (Master’s or PhD preferred)

• 5+ years of experience applying statistical analysis to solve complex business problems

• Strong foundation in statistical inference, regression analysis, hypothesis testing, experimental design, and predictive modeling

• Advanced SQL skills with experience building large-scale analytical datasets

• Proficiency in Python or R for statistical analysis and machine learning

• Experience developing predictive models using techniques such as logistic regression, gradient boosting, random forests, or survival analysis

• Strong understanding of SaaS business metrics including ARR, ACV, CAC, LTV, conversion rates, retention, renewal, and expansion

• Excellent communication skills with the ability to explain complex analytical concepts to technical and non-technical audiences

• Demonstrated ability to influence business strategy through data-driven insights.