Assoc Dir-AI Science

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The Associate Director of AI Science is a highly strategic, business-facing leadership role dedicated to driving commercial value across our Home and Mobility verticals. Sitting at the intersection of advanced machine learning and business strategy, this role focuses on leveraging propensity modeling and dynamic microsegmentation to unlock new revenue streams, optimize the customer lifecycle, and elevate customer lifetime value.

You will act as the crucial bridge between our technical AI Science teams and the Home and Mobility business units, ensuring that complex AI and data science capabilities are translated into adopted, scalable solutions that deliver measurable ROI and continuous business growth.

Key Responsibilities

Business Strategy & Commercial Value Creation

• Monetize AI Capabilities: Lead the strategic application of advanced propensity models (e.g., likelihood-to-buy, churn prediction, next-best-action, cross-sell/up-sell) to drive tangible growth and retention in the Home and Mobility sectors.
• Define Microsegmentation Strategy: Guide the development of highly granular, behavioral microsegments to personalize marketing efforts, optimize pricing strategies, and tailor product offerings in real-time.
• ROI Accountability: Establish frameworks to measure the commercial impact of deployed AI models. Define, track, and report on key performance indicators (KPIs) that demonstrate direct value creation, revenue lift, and cost optimization.
• Lifecycle Optimization: Embed AI-driven insights into critical touchpoints along the customer lifecycle, ensuring predictive interventions are timed perfectly with high-impact trigger events.
  
  

Stakeholder Management & AI Adoption

• Executive Liaison: Serve as the primary strategic advisor and translator between the AI Science function and Home/Mobility business leaders (Marketing, Product, Sales, and Customer Experience).
• Drive Business Adoption: Champion the operationalization of AI models. Overcome organizational silos and resistance by demonstrating clear business value, securing buy-in, and embedding AI tools directly into end-user workflows.
• Storytelling with Data: Translate highly technical machine learning concepts, model performance metrics, and statistical outputs into clear, compelling narratives and strategic recommendations for senior executive leadership.
• Needs Translation: Proactively identify business pain points within Home and Mobility and translate these into actionable data science projects, defining clear modeling requirements for the technical teams.
  
  

Technical Oversight & Cross-Functional Leadership

• Model Lifecycle Strategy: Oversee the business strategy for models deployed in high-impact areas, ensuring continuous optimization, accuracy, and relevance to shifting market dynamics.
• Pipeline Integration: Partner closely with Data Engineering, MLOps, and IT teams to ensure models are seamlessly deployed into production environments and marketing automation platforms.
• Team Mentorship: Provide strategic direction and business-context mentorship to data scientists and AI engineers, ensuring their technical execution remains tightly aligned with corporate objectives.
  
  

Core Competencies & Qualifications

Experience & Education

• Education: Master’s degree in Data Science, Computer Science, Statistics, Business Analytics, or a related field (an MBA with a strong quantitative focus is highly preferred).
• Industry Experience: 8+ years of experience in data science, advanced analytics, or AI strategy, with a minimum of 3 years in a leadership, product management, or business-facing role.
• Domain Knowledge: Deep understanding of the telecommunications, broadband, or consumer technology industries, specifically within Home (e.g., fiber, smart home, IoT) and Mobility (e.g., 5G, wireless services) verticals.
  
  

Technical & Business Skills

• AI/ML Fluency: Strong foundational understanding of machine learning algorithms, deep learning, NLP, and LLM architecture. Must be highly conversant in how techniques utilizing frameworks like PyTorch and scikit-learn are applied to business problems, even if not writing production code daily.
• Advanced Propensity & Segmentation: Proven track record of designing, evaluating, and strategically deploying end-to-end propensity models and clustering techniques for large-scale customer bases.
• Data Stack Familiarity: Experience working with cloud platforms (e.g., GCP, AWS, Azure), production MLOps tools, and large-scale data extraction processes.
• Exceptional Communication: Elite presentation skills with the ability to distill complex analytical findings into actionable business strategies for non-technical stakeholders.
  
  

What Success Looks Like in Year One

• Successfully integrated at least three major propensity or microsegmentation models into the Home and Mobility go-to-market workflows.
• Established a regular cadence of AI performance reporting that clearly demonstrates incremental revenue lift or churn reduction to the executive team.
• Achieved a high adoption rate of AI-driven recommendations among business stakeholders, shifting the organizational culture toward proactive, model-driven decision-making.
  
  

Where you’ll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.