You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.
What you’ll be doing...You will serve as a lead individual contributor within our team of propensity modelers, driving the technical execution of Verizon’s transition to a modern, agile pod model. In this principal-level role, you will operate with a high degree of independence, owning our most complex propensity models and supporting Verizon's highest-priority, highest-visibility base management pods. You will work directly at the critical touchpoints of the customer lifecycle and high-impact trigger events, providing the advanced machine learning support needed to unlock deep microsegmentation and hyper-personalization. Your work will directly empower marketers, optimize customer journeys, and drive down churn across our most critical customer segments.
Building, training, and deploying our most complex and high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers.
Operating independently to manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
Collaborating closely with high-visibility base management pods and senior marketing stakeholders to translate complex business retention goals into actionable data science solutions.
Owning the lifecycle of models deployed in high-impact areas, ensuring continuous optimization, accuracy, and measurable business performance.
Translating advanced analytical outputs into actionable microsegmentation strategies that enable marketing partners to deliver highly personalized customer experiences.
Serving as a technical mentor and advisor to senior and mid-level AI/ML engineers on the team, sharing best practices for model optimization and data pipelines.
Presenting complex model insights, performance metrics, and strategic recommendations clearly to senior leadership and cross-functional business partners.
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 are a highly experienced data science professional who thrives on solving complex analytical problems with minimal guidance. You have a proven track record of managing high-priority machine learning projects, and you excel at collaborating directly with business partners to deliver data-driven customer experiences that impact the bottom line.
You will need to have:
Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Four or more years of experience independently developing, deploying, and optimizing complex machine learning or propensity models in a production environment.
Experience working on high-priority or high-visibility technical initiatives within a corporate setting.
Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
Even better if you have one or more of the following:
Master’s degree in Data Science, Computer Science, Statistics, or a highly quantitative field.
Knowledge of LLM agent architecture: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG , MCP, A2A protocols.
Experience with retrieval-augmented generation (RAG), ONNX-based embeddings, vector databases and semantic search
Knowledge of cloud-scale data engineering: BigQuery pipelines, GCP (Cloud Run, Vertex AI).
Strong domain expertise in customer retention strategies, churn prediction, or customer lifetime value (CLV) modeling.
Experience designing and evaluating A/B tests for models in production, production ML/LLM monitoring and observability tooling (e.g., OpenTelemetry, Arize Phoenix, Galileo) for tracking model drift, accuracy degradation, or output quality over time
Experience operating within an agile, pod-based operating model, directly supporting marketing or customer experience teams.
Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.
Excellent communication and presentation skills, with a demonstrated ability to explain advanced predictive models to non-technical stakeholders.
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.
Benefits and CompensationOur benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit 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. We also offer a 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, plus other incentives, we’ve got you covered with our award-winning total rewards package. 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. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.
The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours.The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $120,500.00 - $231,000.00.Skills Required
- Bachelor's degree or four or more years of work experience.
- Six or more years of relevant experience.
- Four or more years independently developing, deploying, and optimizing complex machine learning or propensity models in production.
- Experience working on high-priority or high-visibility technical initiatives within a corporate setting.
- Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
- Experience managing end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
- Master's degree in Data Science, Computer Science, Statistics, or a highly quantitative field.
- Knowledge of LLM agent architecture (Google ADK, LangChain/LangGraph), multi-agent orchestration, RAG, MCP, A2A protocols.
- Experience with retrieval-augmented generation (RAG), ONNX-based embeddings, vector databases, and semantic search.
- Knowledge of cloud-scale data engineering: BigQuery pipelines, GCP (Cloud Run, Vertex AI).
- Strong domain expertise in customer retention strategies, churn prediction, or CLV modeling.
- Experience designing and evaluating A/B tests for models in production and using ML/LLM observability tooling (OpenTelemetry, Arize Phoenix, Galileo).
- Experience operating within an agile, pod-based operating model supporting marketing or customer experience teams.
- Experience with cloud platforms (GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.
- Excellent communication and presentation skills, with ability to explain advanced predictive models to non-technical stakeholders.
Verizon Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Verizon and has not been reviewed or approved by Verizon.
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Fair & Transparent Compensation — Fairness and competitiveness of pay are highlighted through statements such as “pay is good,” “pays very well,” and “the compensation at VZ is very competitive.” High earning potential is also described for certain roles, including base pay plus commissions and bonuses.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive, spanning medical, dental, and vision with before-tax contributions and preventive-care credits. Increased HSA contributions and multiple plan options further reinforce the perceived strength of health benefits.
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Retirement Support — Retirement offerings are positioned as robust, including a strong 401(k) match, pension eligibility for some groups, and additional financial protections like life and long-term disability coverage. Union contract updates also point to pension increases and retirement security improvements.
Verizon Insights
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Why Work With Us
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