Senior AI Engineer

What You’ll Be Doing

You will join a dynamic team of propensity modelers dedicated to supporting Verizon's base management organization as it transitions to an agile pod model. As an essential member of this team, you will be assigned to a specific base management pod focused on key moments in the customer lifecycle and specific trigger events. In this role, you will be providing advanced machine learning modeling support that empowers our pods and marketing partners to unlock microsegmentation and high-level personalization, directly driving down customer churn and maximizing lifetime value.

Responsibilities

• Developing, training, and deploying advanced propensity models to predict customer behaviors, churn risk, and lifecycle triggers.
• Collaborating cross-functionally with assigned base management pods to translate complex business problems into actionable data science solutions.
• Unlocking microsegmentation and personalization strategies by translating model outputs into tailored customer journeys for marketing execution.
• Monitoring, evaluating, and refining model performance over time to ensure high accuracy, relevancy, and business impact.
• Partnering with technology and data engineering teams to scale machine learning workflows and production systems.
• Communicating complex analytical concepts and model insights clearly to business partners and executive stakeholders.

Where you'll be working

This hybrid role will have a defined work location that includes work from home and assigned office days as set by the manager.

What We’re Looking For

You enjoy working in a collaborative, fast-paced environment and have a passion for transforming complex data into highly personalized customer experiences. You thrive when tackling challenging analytical problems and are energized by the opportunity to directly impact business outcomes like customer retention and engagement.

You'll Need To Have

• Bachelor's degree or four or more years of work experience.
• Four or more years of relevant experience required, demonstrated through work experience and/or military experience.
• Experience building, deploying, and maintaining predictive models 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.

Even better if you have one or more of the following

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
• 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 working in an Agile environment or within cross-functional, pod-based operating models.
• Experience with cloud platforms such as GCP, AWS, or Azure, and cloud-native machine learning tools (e.g., Vertex AI, SageMaker).
• Experience with machine learning framework ecosystems (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Strong communication skills with the ability to explain complex machine learning models and metrics to non-technical stakeholders.

Benefits

• Health and wellness options including medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance
• Matched 401(k) savings plan
• Up to 8 company paid holidays per year and up to 6 personal days per year
• Paid parental leave, adoption assistance and tuition assistance
• Newly hired employees receive up to 15 days of vacation per year, which grows with additional service
• Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc.

Pay

The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $101,000.00 - $194,000.00. This is an incentive based position with the potential to earn more. The salary will vary depending on your location and confirmed job-related skills and experience.

Schedule

In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies. Scheduled Weekly Hours 40.

This response is AI-generated, for reference only.