Lead Data Scientist - Marketing Measurement

As a Lead Data Scientist specializing in Marketing Measurement and Experimentation, your role will involve building production-grade impact measurement models for Digital Experience Platforms and email campaigns. You will be responsible for quantifying incremental lift across sales, revenue, conversions, and engagement, and enabling feature-level attribution across various marketing elements. • *Key Responsibilities:** - Build models to measure incremental lift from website/app features and email campaigns. - Provide granular attribution across banners, journeys, UI components, and ads. - Design and analyze A/B experiments and causal inference frameworks. - Develop production-ready statistical and ML models (A/B testing, causal inference, uplift modeling, Markov chains). - Build automated pipelines for data processing, model scoring, monitoring, and retraining. - Deliver robust validation reports with performance metrics. - Translate complex analyses into clear, actionable insights for senior stakeholders. - Partner with Marketing, Product, Engineering, and Analytics teams. • *Key Deliverables:** - Production-grade Python / PySpark code for impact measurement models. - Validation and testing documentation with performance metrics. - Automated pipelines for scoring, monitoring, and retraining. - Impact dashboards and executive-ready insights. • *Required Skills:** - 6+ years of experience in Data Science. - Strong experience in Marketing Measurement & Experimentation. - Expertise in statistical modeling, causal inference, A/B testing, uplift modeling, and Markov chains. - Strong hands-on experience with Python and PySpark. - Experience building scalable production ML pipelines. - Strong communication and stakeholder management skills. - Ability to lead complex analytical initiatives independently. As a Lead Data Scientist specializing in Marketing Measurement and Experimentation, your role will involve building production-grade impact measurement models for Digital Experience Platforms and email campaigns. You will be responsible for quantifying incremental lift across sales, revenue, conversions, and engagement, and enabling feature-level attribution across various marketing elements. • *Key Responsibilities:** - Build models to measure incremental lift from website/app features and email campaigns. - Provide granular attribution across banners, journeys, UI components, and ads. - Design and analyze A/B experiments and causal inference frameworks. - Develop production-ready statistical and ML models (A/B testing, causal inference, uplift modeling, Markov chains). - Build automated pipelines for data processing, model scoring, monitoring, and retraining. - Deliver robust validation reports with performance metrics. - Translate complex analyses into clear, actionable insights for senior stakeholders. - Partner with Marketing, Product, Engineering, and Analytics teams. • *Key Deliverables:** - Production-grade Python / PySpark code for impact measurement models. - Validation and testing documentation with performance metrics. - Automated pipelines for scoring, monitoring, and retraining. - Impact dashboards and executive-ready insights. • *Required Skills:** - 6+ years of experience in Data Science. - Strong experience in Marketing Measurement & Experimentation. - Expertise in statistical modeling, causal inference, A/B testing, uplift modeling, and Markov chains. - Strong hands-on experience with Python and PySpark. - Experience building scalable production ML pipelines. - Strong communication and stakeholder management skills. - Ability to lead complex analytical initiatives independently.