Associate Director, Data Science

Verizon•Basking Ridge, NJ

3d•$126,000 - $242,000•Hybrid

About The Position

As the Associate Director of Modeling & Decision Intelligence, you will lead an elite advanced analytics team partnering with our Global Supply Chain, Sourcing, Global Real Estate, Global Network & Technology and Fleet organizations. You will be the strategic architect responsible for moving our operations away from manual, reactive decision-making and toward a proactive, autonomous ecosystem. You will work with key stakeholders to generate hypotheses and create analytic models that answer our most impactful business questions. You are responsible for leading the design of data science products while thinking strategically about how these models meet the long-term goals of the business. You will leverage our full tech stack to develop resolutions to complex problems that require creativity, making decisions that directly impact Verizon's performance, predictability, and operational efficiency across multiple enterprise domains. You will not just manage daily operations; you will also shape the roadmap for how Verizon uses data to drive massive P&L impact across our network, asset, and infrastructure footprint. You will lead the development of precision engines—such as localized store/SKU demand sensing, margin optimization for returned devices, spatial DC network analysis, and real estate and fleet asset optimization—and act as the ultimate bridge between technical capability and executive-level business strategy.

Requirements

Bachelor’s degree or four or more years of work experience.
Eight or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Experience in data science, with a proven track record in Supply Chain Analytics, Mathematical Optimization, or Predictive Modeling.
Leadership experience managing and developing a team of data scientists and/or quantitative researchers.
Deep proficiency in Python, SQL, and advanced statistical modeling.

Nice To Haves

Master’s degree or PhD in Operations Research, Industrial Engineering, Statistics, Economics, or a related quantitative field.
Strong business and financial acumen, with a demonstrated ability to tie analytical model outcomes directly to financial metrics (CapEx/OpEx reduction, ROI, and P&L impact).
Functional understanding or experience working with data structures from core enterprise platforms like SAP S/4HANA (S4) (for real-time Supply Chain/Sourcing ERP) and IBM TRIRIGA (for Real Estate & Facilities Portfolio Management).
Experience with geospatial analysis, routing optimization, or location intelligence frameworks (e.g., GeoPandas, Kepler.gl, or GIS tools) applied to network or fleet logistics.
Experience with large-scale mathematical optimization solvers, specifically Gurobi or CPLEX.
Experience managing enterprise-grade data science lifecycles within platforms like Domino Data Lab.
AI-Native Workflow Experience: Familiarity with integrating LLMs, RAG architectures, or advanced coding assistants (e.g., Claude Code, Cursor) into data science workflows to accelerate delivery.
Expertise in interactive visualization and delivery frameworks, such as Plotly, Streamlit, or Tableau, to democratize model consumption.
Strong executive communication and negotiation skills, with a demonstrated ability to influence senior business stakeholders.

Responsibilities

Strategic Leadership & Decision Design: Direct the team toward high-ROI business problems. Elevate data science from standard "predictive modeling" to Decision Intelligence, ensuring technical outputs are directly translated into actionable business cases for senior executives (e.g., inventory optimization, spend analytics, and procurement risk mitigation).
Team Evolution & Mentorship: Lead, inspire, and upskill a high-performing team of data scientists and optimization engineers. Conduct regular technical and professional code/design reviews, fostering an environment that embraces AI-native development.
Scale the Tech Stack & Innovation: Stay at the frontier of AI and advanced analytics. Guide the team in leveraging modern tools (Gurobi, Domino Data Lab, VS Code) and emerging technologies (LLMs, RAG, Agentic workflows) to build robust, scalable analytics products.
Stakeholder Influence & Translation: Serve as a trusted advisor to senior leadership across Supply Chain, GN&T, Fleet, and Real Estate. Master the art of Executive Storytelling, translating deep statistical and mathematical programming outputs into clear strategic narratives.
Ecosystem Governance: Oversee the end-to-end lifecycle of the team’s models, ensuring that production-grade systems are governed, bias-free, reproducible, and seamlessly integrated into the business's consumption layer.