Data Scientist, Revenue Analytics

Jobtailor; Deutschland; Remote; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior data scientist to develop statistical models and analytics across marketing, sales, and customer success, focusing on pipeline performance and ARR. You will build predictive models, run experiments, and communicate insights to leadership to guide strategic investments.

You will collaborate with cross-functional teams, design experiments, and improve data quality and measurement practices, driving data-driven decisions across the organization.

Qualifikationen

• Bachelor's degree in a quantitative field; advanced degree preferred.
• 5+ years applying statistical analysis to business problems.
• Strong foundation in inference, regression, hypothesis testing, experimental design, and predictive modeling.
• Advanced SQL skills for large datasets.
• Proficiency in Python or R for statistics and ML.
• Experience with predictive modeling (logistic regression, gradient boosting, random forests, survival).
• Understanding SaaS metrics: ARR, CAC, LTV, retention, renewal, expansion.
• Excellent communication with both technical and non-technical audiences.
• Ability to influence strategy with data-driven insights.

Aufgaben

• Develop statistical models and analytical frameworks to measure impact on pipeline, bookings, ARR, renewal, and expansion.
• Analyze paid media effectiveness: ROAS, CAC, and ROI.
• Build predictive models for drivers of CAC, conversions, retention, and churn.
• Design experiments to measure incremental business impact and guide investments.
• Collaborate with cross-functional teams to define success metrics and measurement strategies.
• Develop forecasting models to support revenue planning.
• Communicate findings to senior leaders with data visualizations and storytelling.
• Improve data quality and analytical best practices across the organization.

Kenntnisse

Statistical analysis

SQL

Python

R

Machine learning

Data visualization

Communication

Storytelling

Cross-functional collaboration

Ausbildung

Bachelor’s degree in a quantitative field

Master’s or PhD preferred

Tools

Python

R

SQL

Pandas

Jobbeschreibung

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.