Senior Data Scientist

Role overview

• Develop, implement, and maintain predictive and propensity models to forecast customer behavior, including purchase likelihood, churn risk, and campaign responsiveness.
• Apply statistical and machine learning techniques to large-scale datasets to drive measurable business outcomes.
• Design, validate, and monitor models to ensure ongoing performance, reliability, and business relevance.
• Translate model outputs into actionable business strategies that improve conversion, retention, and lifetime value.
• Partner with marketing and product teams to optimize campaign performance through data-driven insights.
• Design and execute A/B tests and other controlled experiments to measure incremental impact and improve marketing effectiveness.
• Identify opportunities to improve targeting, segmentation, and personalization strategies.
• Balance speed, cost, and analytical rigor to support timely business decisions.
• Ensure data integrity, quality, and compliance with applicable privacy regulations (including GDPR and CCPA).
• Build dashboards, reports, and visualizations that clearly communicate findings to technical and non-technical stakeholders.
• Challenge assumptions, surface risks, and provide independent analytical perspective to senior leadership.
• Maintain strong documentation and governance practices across models and analyses.
• Not a purely reporting or dashboard-production role.
• Not a junior or supervised modeling position.
• Not a data engineering or infrastructure-only role.
• Not a theoretical research position detached from business impact.
• Not a marketing execution role without analytical ownership.
• 5+ years of experience in data science, marketing analytics, or a related quantitative role, preferably in a B2C subscription or performance-driven environment.
• Proven experience building and deploying predictive models, including logistic regression, tree-based models, and gradient boosting techniques.
• Strong proficiency in Python or R for data analysis and modeling.
• Advanced SQL skills for querying and manipulating large datasets.
• Experience designing and interpreting experiments, including A/B testing and causal analysis.
• Strong understanding of statistical methods, machine learning algorithms, and model validation techniques.
• Experience translating analytical findings into strategic recommendations for business stakeholders.
• Ability to operate independently in a fast-paced, cross-functional environment.
• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.

About the company