What you’ll be doing...

At Verizon, Finance is leading the formation of an advanced analytics arm that delivers world-class insights in driving business impacts through a data driven approach. This is a unique opportunity to be a part of a growing team in a fast-paced and evolving environment that works in close partnership with internal business partners to inform business strategies via advanced analytics. We’re finding new ways to add value and provide strategic support and we want passionate and talented analytics practitioners to join us and be a catalyst for change.

As the Principal, you will drive better business results via actionable insights and will be an analytics business partner to Marketing Strategy and Consumer & Business segment teams in delivering the “Get Them, Grow Them and Delight Them” objectives for the wireless business. You will be involved in pricing decisions, promotion and offer optimization, device economics, product & customer profitability, omni-channel strategy and new initiatives to improve business efficiency through analytics driven decision management.

This role requires you to drive predictive and prescriptive analytics to guide and support strategic decisions on Value Based Marketing & Digital Transformation, leverage machine learning techniques to optimize Credit decisions and Fraud detection and identify new opportunities to drive the business growth through rapid simulation using customer behavioral data science.

You will interact with all HQ & Market departments including Marketing, Digital, Media, Credit Risk, Fraud, UX/CX, IT Finance and Network. Some of the high level focus areas for the role include:

Analytical Work Management:

  • Partner with internal business partners in gathering business requirements and developing advanced analytical solutions to complex problems
  • Hands on active participation in analytical projects delivering improvements in decision-making and business strategies via advanced analytics
  • Participate in the design, implementation and interpretation of experiments/trials for continuous refinement of on-going strategies
  • Translate predictive insights from complex analytical framework to marketing investment optimization
  • Prepare presentation materials and formal business case documents for use with senior management to promote findings and drive science based decision support recommendations

Modeling & Infrastructure:

  • Develop and deploy both traditional statistical models and machine learning techniques and algorithms: Regression, clustering, neural networks, Anomaly Detection, Random Forest etc. to guide marketing investments and strategy
  • Ability to develop advanced analytics in multiple platforms including Hadoop Clusters as well as Teradata
  • Partner with in-house data strategy experts to design analytically ready datasets by stitching customer data across multiple platforms and incorporating business rules
  • Periodically validate model performance and update models based on changing business strategies/objectives


  • Develop strong relationships with business partners to transform the role of analytics to decision guidance (analytics as partner not as support function)
  • Partner with functional groups (Marketing, IT, Commercial Finance, Operations, Network, etc.) to embed analytics and science driven approach in all business decisions
  • Be recognized as a subject matter expert and participate in knowledge/best practice sharing opportunities
  • Continually broaden and strengthen knowledge of analytical methods, vendors and tools

What we’re looking for...

You have a high level of curiosity and investigative mind-set with an attention to detail, a tenacity of thought, the flexibility to adapt to new challenges and the resiliency to overcome short-term hurdles by staying focused on the team's deliverables. You have a passion for educating and communicating analytic findings and insights with integrity to all levels. You also have a voracious appetite for improvement of our analytical products and processes built on a solid foundation of a lifelong love of learning.

You’ll need to have:

  • Bachelor’s degree or four or more years of work experience.
  • Six or more years of relevant work experience.
  • Experience developing and implementing advanced analytical solutions to complex business problems/opportunities.

Even better if you have:

  • Master’s degree in Mathematics, Statistics, Financial, Economics/Econometrics, Computer Science, Operations Research or related discipline.
  • Experience working in the Consumer/Retail space within the Financial Services, Telecommunications, and Technology or related work in the Public Policy, Bio-statistics and Scientific Research industries.
  • Experience with Hadoop Clusters/Hive/Spark/Scala
  • Publication of technical papers for, and/or attendance and participation in organizations such as SAS Users Groups, Informs, American Statistical Association, ML Forums or others.
  • Experience with Data management, analysis and visualization to realize absolute and incremental commercial gains
  • Experience inone of SAS/R/Python and experience to programing in SQL, VBA, SPSS, MATLAB, JAVA, Tableau or other related tools.

When you join Verizon...

You’ll be doing work that matters alongside other talented people, transforming the way people, businesses and things connect with each other. Beyond powering America’s fastest and most reliable network, we’re leading the way in broadband, cloud and security solutions, Internet of Things and innovating in areas such as, video entertainment. Of course, we will offer you great pay and benefits, but we’re about more than that. Verizon is a place where you can craft your own path to greatness. Whether you think in code, words, pictures or numbers, find your future at Verizon.

Equal Employment Opportunity

We're proud to be an equal opportunity employer- and celebrate our employees' differences,including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, and Veteran status. Different makes us better.