What you’ll be doing...

Our HR Business Intelligence team seeks a data scientist (including machine learning, analytics, 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, machine learning 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 or four or more years of work experience.
  • Four or more years of relevant work experience.
  • Two or more years of experience in developing and implementing machine learn models in business setting.
  • Willingness to travel.

Even better if you have:

  • Bachelor’s degree in Data Science/Analytics, Computer Science, Operations Research, Applied Statistics, or a related field with emphasis on quantitative methods.
  • Familiarity and experience with data visualization software such as Qlik or Tableau.
  • Familiarity 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.
  • Ability to condense and structure large datasets for analytics.
  • Strong analytical, critical thinking and decision‐making skills.
  • Ability to work independently and effectively manage concurrent projects, multiple priorities, and make trade-offs to deliver effective solutions in a timely fashion.
  • Strong project management, negotiation, and influencing skills.
  • High professional standards for customer service, confidentiality, integrity, and quality of work.
  • Experience with both structured and unstructured data.

When you join Verizon...

You’ll have the power to go beyond – doing the work that’s transforming how people, businesses and things connect with each other. Not only do we provide the fastest and most reliable network for our customers, but we were first to 5G - a quantum leap in connectivity. Our connected solutions are making communities stronger and enabling energy efficiency. Here, you’ll have the ability to make an impact and create positive change. Whether you think in code, words, pictures or numbers, join our team of the best and brightest. We offer great pay, amazing benefits and opportunity to learn and grow in every role. Together we’ll go far.

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.