Director, AI & Machine Learning Engineering

• Lead a sophisticated team of propensity modelers supporting the base management organization’s transition to an agile pod model
• Lead the modeling chapter and deploy data scientists across cross-functional base management pods
• Optimize customer lifecycle stages and critical trigger events
• Partner with marketing and business leadership to deliver machine learning and modeling capabilities
• Drive microsegmentation and hyper-personalization to reduce customer churn
• Orchestrate strategic hiring, talent development, technical training, resource management, and process improvement
• Establish, elevate, and audit enterprise modeling standards and governance
• Lead collaboration with business transformation, technology, finance, and advanced analytics teams
• Create and deliver executive presentations translating AI science strategies into business narratives

• Bachelor's degree or four or more years of work experience
• Ten or more years of relevant work experience
• Experience leading teams of data scientists or predictive modelers
• Experience with customer lifecycle marketing, base management, or churn mitigation strategies
• Experience with agile delivery frameworks or pod-based operating models
• Willingness to travel up to approximately 25% of the time
• Master's degree or PhD in data science, statistics, computer science, or a related quantitative field preferred as an “even better” qualification
• Expert-level knowledge of advanced propensity modeling, machine learning algorithms, and personalization architectures
• Experience with large-scale cloud data platforms such as Google Cloud Platform, AWS, or Azure
• Proficiency in enterprise-level modeling standards, model governance, and process automation frameworks
• Executive communication and storytelling skills bridging technical AI concepts and commercial business outcomes

Demonstrates expertise in leading data science teams and implementing advanced propensity modeling and machine learning strategies to enhance customer lifecycle management and reduce churn. Proficient in executive communication, translating complex AI concepts into actionable business insights.

• Advanced Propensity Modeling
• Machine Learning Algorithms
• Customer Lifecycle Marketing
• Agile Delivery Frameworks
• Executive Communication

• Data Science
• Predictive Modeling
• Process Automation
• Model Governance
• Microsegmentation
• Hyper-Personalization
• Statistical Analysis
• Quantitative Analysis
• Churn Mitigation Strategies
• Technical Training

• Leadership
• Collaboration
• Storytelling
• Talent Development
• Resource Management

• Master's Degree in Data Science
• PhD in Data Science

• Base Management
• Customer Churn
• Agile Pod Model
• Enterprise Modeling Standards
• Business Transformation

• Google Cloud Platform
• AWS
• Azure