Lead Propensity AI Engineer for Personalization

Verizon Communications; Basking Ridge (NJ); Hybrid; USD 120,500 - 231,000; Full time

Benefits offered by this job

Health benefits

401(k) matching

Paid time off

Tuition assistance

Job summary

Verizon Communications is seeking a highly experienced data science professional to lead propensity modeling within a modern, agile pod setup. You will own complex models, drive end-to-end pipelines, and collaborate with marketing to optimize customer journeys.

The role involves mentoring engineers, translating business goals into data solutions, and presenting insights to senior leadership. This hybrid position includes home and office days in a defined location.

Qualifications

• Bachelor’s degree or four or more years of work experience.
• Experience leading high-priority ML projects and collaborating with partners.
• Production experience deploying complex ML/propensity models.
• Knowledge of cloud-scale data engineering and ML tooling.
• Strong communication and ability to explain model insights to non-technical stakeholders.

Responsibilities

• Lead the most complex propensity models and high-visibility pods.
• Develop end-to-end model pipelines from feature engineering to deployment.
• Collaborate with marketing stakeholders to translate goals into data solutions.
• Own model lifecycle, monitoring, and continuous optimization.
• Mentor senior and mid-level engineers on data pipelines and ML practices.
• Present insights and recommendations to leadership.

Skills

Python

R

SQL

Machine learning

Propensity models

LLM architecture

LangChain

Vertex AI

BigQuery

GCP

ONNX

Education

Bachelor’s degree

Master’s degree

Tools

LangChain

LangGraph

OpenTelemetry

Arize Phoenix

Galileo

ONNX

BigQuery

Vertex AI

Google ADK

Job description

Verizon Communications is seeking a highly experienced data science professional to lead propensity modeling within a modern, agile pod setup. You will own complex models, drive end-to-end pipelines, and collaborate with marketing to optimize customer journeys.

The role involves mentoring engineers, translating business goals into data solutions, and presenting insights to senior leadership. This hybrid position includes home and office days in a defined location.