What you’ll be doing...

HR Data & Analytics team seeks an expert in data analysis (including data structuring, mining, modeling, and visualization) with strong project management skills, to drive strategic workforce initiatives and enable decision-making to optimize attraction, productivity, engagement, and retention of workforce at Verizon.

  • Analyze the needs of internal clients to prioritize, develop, and execute project plans to identify initiatives and manage partner agreements, deliverables and timetables.
  • Effectively formulate business and workforce problems to design and implement creative solutions through analytics and predictive modeling
    • Identify data sources and build data sets to perform statistical analyses
    • Perform model assessment, validation, and enhancement activities
    • Create what-if scenarios and develop algorithms to forecast and predict workforce behavior
    • Evaluate effectiveness of processes and measure the impact and ROI of changes associated with recommend solutions
  • Generate and disseminate actionable data, insights, and recommendations through clear, succinct reports and presentations to senior leadership and stakeholders to drive strategic workforce initiatives and HR operations
  • Partner with IT/HRIS to effectively migrate analytical models from prototype to production
  • Drive understanding, adoption and application of analytical model results with end-users by translating technical findings into simple and succinct readouts to stakeholders
  • Maintain working knowledge of modeling, data mining and visualization best practices; keep current on the latest trends and best practices in HR and workforce analytics
  • Engage with broader team and promote cross-functional and cross-business knowledge sharing and internal analytics talent development

What we’re looking for...

You'll need to have:

  • Bachelor’s degree in Operations Research, Applied Statistics, or a related field with emphasis on quantitative methods.
  • Six or more years of relevant work experience.

Even better if you have:

  • Master's degree in Operations Research, Applied Statistics, or a related field with emphasis on quantitative methods
  • Coding skills in a general-purpose programming language (e.g., Python)
  • Four or moreyears of experience in developing and implementing statistical models in business setting.
  • Experience with both structured and unstructured data
  • Ability to condense and structure large datasets for analytics
  • Three or moreyears of experience with SQL and statistical software packages (R, SAS, or SPSS)
  • Strong verbal, written communication and interpersonal skills to articulate linkage between business needs and analytical findings
  • Strong analytical, critical thinking and decisionmaking skills
  • Strong project management, negotiation, and influencing skills
  • Ability to work independently and effectively manage concurrent projects, multiple priorities, and make trade-offs to deliver effective solutions in a timely fashion
  • High professional standards for customer service, confidentiality, integrity, and quality of work
  • Familiarity and experience with data visualization software such as Qlik or Tableau

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.