Senior AI Engineer

Verizon

Senior AI Engineer developing predictive models that reduce churn and personalize customer journeys for Verizon’s telecommunications business. Deploying machine learning systems and translating insights into marketing action.

Posted 8/5/2026full-timeBasking Ridge • New Jersey, Texas • 🇺🇸 United StatesSenior💰 $101,000 - $194,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying predictive models using Python, R, and SQL, while effectively communicating insights to stakeholders. Proficient in leveraging cloud platforms and machine learning tools to enhance customer lifecycle strategies and churn prevention.

Highest-signal resume keywords

Predictive Model DevelopmentPython ProgrammingSQL Database TechnologiesMachine Learning ToolsCloud Platforms (GCP, AWS, Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingData ScienceMachine LearningStatistical AnalysisData Manipulation

Soft Skills

CommunicationCollaborationProblem-Solving

Tools & Technologies

Google BigQueryVertex AISageMakerTensorFlowPyTorch

Certifications & Qualifications

Bachelor's DegreeMaster's Degree or Ph.D. in Data Science or Related Field

Industry Keywords

Customer LifecycleChurn PreventionAgile EnvironmentMicrosegmentationPersonalization Strategies

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop, train, and deploy advanced propensity models predicting customer behaviors, churn risk, and lifecycle triggers
Collaborate with assigned base management pods to translate business problems into actionable data science solutions
Translate model outputs into microsegmentation, personalization strategies, and tailored customer journeys for marketing execution
Monitor, evaluate, and refine model performance to maintain accuracy, relevancy, and business impact
Partner with technology and data engineering teams to scale machine learning workflows and production systems
Communicate analytical concepts and model insights to business partners and executive stakeholders

Requirements

What you’ll need

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 building, deploying, and maintaining predictive or propensity models in a production environment
Experience with Python, R, or similar programming languages for data science and machine learning
Experience with SQL and database technologies for large-scale data manipulation and extraction
Master's degree or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field preferred as an “even better” qualification
Knowledge of LLMs, RAG, Google ADK, and LangGraph
Experience with Google BigQuery
Knowledge of base management structures, customer lifecycle stages, or churn prevention strategies
Experience in an Agile environment or cross-functional, pod-based operating models
Experience with GCP, AWS, or Azure and cloud-native machine learning tools such as Vertex AI or SageMaker
Experience with TensorFlow, PyTorch, or Scikit-Learn ecosystems
Ability to explain complex machine learning models and metrics to non-technical stakeholders

Benefits

Comp & perks

Medical, dental, and vision benefits
Short- and long-term disability insurance
Basic and supplemental life insurance
AD&D insurance
Identity theft protection
Pet insurance
Group home and auto insurance
Matched 401(k) savings plan
Up to 8 company-paid holidays per year
Up to 6 personal days per year
Paid parental leave
Adoption assistance
Tuition assistance
Other incentives
Potential premium pay such as overtime, shift differential, holiday pay, and allowances
Up to 15 days of vacation per year for newly hired employees, increasing with additional service