Director, AI & Machine Learning Engineering

Jobtailor; New Jersey; On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor in New Jersey seeks a seasoned data science leader to guide propensity modeling and ML initiatives across cross-functional pods. You will optimize lifecycle stages, drive personalization, and partner with marketing to reduce churn.

The role requires extensive experience in advanced modeling, cloud data platforms, and executive storytelling to align AI strategies with business outcomes.

Qualifications

• Bachelor's degree or four+ years of work experience required.
• Ten+ years of relevant work experience preferred.
• 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 ~25%.
• Master's or PhD in data science or related quantitative field preferred.
• Expert-level knowledge of propensity modeling, ML algorithms, and personalization architectures.
• Experience with large-scale cloud data platforms (GCP/AWS/Azure).
• Proficiency in modeling standards, governance, and automation frameworks.
• Executive communication bridging AI and business outcomes.

Responsibilities

• Lead a 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 pods.
• Optimize customer lifecycle stages and critical trigger events.
• Partner with marketing and business leadership to deliver ML and modeling capabilities.
• Drive microsegmentation and hyper-personalization to reduce churn.
• Oversee hiring, talent development, training, resource management, and process improvement.
• Establish and audit enterprise modeling standards and governance.
• Collaborate with transformation, technology, finance, and analytics teams.
• Create executive presentations translating AI strategies into business narratives.

Skills

Advanced Propensity Modeling

Machine Learning Algorithms

Customer Lifecycle Marketing

Agile Delivery Frameworks

Executive Communication

Education

Bachelor's degree

Master's in Data Science

PhD in Data Science

Tools

Google Cloud Platform

AWS

Azure

Job description

• 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

Requirements

• 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

Core Competencies

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.

Highest-signal resume keywords

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

ATS Optimization Keywords

Hard Skills

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

Soft Skills

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

Certifications & Qualifications

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

Industry Keywords

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

Tools & Technologies

• Google Cloud Platform
• AWS
• Azure