Senior Engineer Consultant – AI​/ML Engineering

• Build, train, and deploy complex, high-priority propensity models predicting customer behaviors, churn risk, and lifecycle triggers
• Manage end-to-end model development pipelines from advanced feature engineering through production deployment and monitoring
• Collaborate with base management pods and senior marketing stakeholders to translate retention goals into data science solutions
• Own the lifecycle of high-impact models, ensuring continuous optimization, accuracy, and measurable business performance
• Translate analytical outputs into microsegmentation strategies for personalized customer experiences
• Present model insights, performance metrics, and strategic recommendations to senior leadership and cross-functional business partners
• Provide advanced machine learning support for Verizon’s transition to a modern, agile pod model
• Support customer lifecycle and trigger-event initiatives to empower marketers, optimize customer journeys, and reduce churn

• Bachelor's degree or four or more years of work experience
• Four or more years of relevant experience, demonstrated through work experience and/or military experience
• Experience with high-priority or high-visibility technical initiatives in a corporate setting
• Knowledge of LLM agent architecture, including Google ADK, Lang Chain/Lang Graph, multi-agent orchestration, RAG, MCP, and A2A protocols
• Experience with retrieval-augmented generation, ONNX-based embeddings, vector databases, and semantic search
• Knowledge of cloud-scale data engineering, including Big Query pipelines and GCP Cloud Run and Vertex AI
• Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction
• Preferred:
  Master’s degree in Data Science, Computer Science, Statistics, or a highly quantitative field
• Preferred:
  Domain expertise in customer retention, churn prediction, or customer lifetime value modeling
• Preferred:
  Experience designing and evaluating A/B tests for production models
• Preferred:
  Experience with production ML/LLM monitoring and observability tools such as Open Telemetry, Arize Phoenix, or Galileo
• Preferred:
  Experience with agile, pod-based operating models supporting marketing or customer experience teams
• Preferred:
  Experience with cloud platforms such as GCP, AWS, or Azure and production MLOps tools
• Preferred:
  Excellent communication and presentation skills for explaining predictive models to non-technical stakeholders

Demonstrates expertise in building and deploying advanced propensity models, utilizing machine learning techniques and cloud-scale data engineering to optimize customer retention strategies. Proficient in translating complex analytical insights into actionable business recommendations for diverse stakeholders.

• Propensity Model Development
• Machine Learning Support
• Cloud-Scale Data Engineering
• Python, R, and SQL Proficiency
• Customer Retention Expertise

• Advanced Feature Engineering
• Statistical Modeling
• A/B Testing Design
• Model Monitoring and Observability
• Data Extraction

• Excellent Communication
• Presentation Skills

• Bachelor's Degree
• Master's Degree in Data Science or Related Field

• Churn Prediction
• Customer Lifetime Value Modeling
• Agile Operating Models
• Multi-Agent Orchestration
• Retrieval-Augmented Generation

• Google ADK
• Lang Chain
• Big Query
• GCP Cloud Run
• Vertex AI