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Job Details


Verizon Communications Inc

Principal Data Scientist - Engineering Analytics

Engineering and Architecture

Architectural Engineering

No

Orlando, Florida, United States

When you join Verizon

Verizon is one of the world’s leading providers of technology and communications services, transforming the way we connect across the globe. We’re a diverse network of people driven by our shared ambition to shape a better future. Here, we have the ability to learn and grow at the speed of technology, and the space to create within every role. Together, we are moving the world forward – and you can too. Dream it. Build it. Do it here.

What you’ll be doing...

The Engineering Analytics Data Science Team has an immediate opening for a talented and experienced Principal Data Scientist with hands on expertise using large datasets to find opportunities for network operation and capital efficiency optimization and using models to test different courses of actions besides a strong interest in understanding the Telecom business model in particular and a passion for data in general. The responsibility of the expert filling up the role is to perform cross-disciplinary analysis, visualization and optimization of traditional, financial, spatial and network data to help solve complex business problems. The successful candidate must have strong experience using a variety of data mining methods, data tools, using, building and implementing predictive models, optimization algorithms, prescriptive models, as well as creating and running simulation. They must have a proven track record of driving business decisions by providing actionable insights based on data. They also must be comfortable working with a wide range of stakeholders and functional teams with the ability to frame problems out of ambiguity and unstructured information.

  • Willing to work in an interdisciplinary field, together with computer scientists, business executives, and telecom network engineers, and will require excellent interpersonal and communication skills.
  • Lead engagements with key business stakeholders in business strategies and opportunities with a focus on driving measurable value via innovative technical solutions to business problems.
  • Build strong working relationships and develop deep partnership with the business.
  • Lead the design and development of machine learning / optimization algorithms, continuously monitoring the model performance and enhancing the algorithms.
  • Integrate multiple data sources, models, and software tools with business line specific decision support and data analysis. This will include the use of distributed computing and utilization of both cloud internal computing resources.
  • Work closely with engineers to deploy models in production for business partners to use and continuously gather feedback from business partners for ease-to-use.
  • Be a subject matter expert on machine learning and predictive modeling and a mentor to junior data scientists
  • Create and walk through executive presentations that explain the complex data and algorithms used in simple easy-to-understand visually striking layman terms that leave a residual impact on an executive audience.
  • Keep current on latest computing trends and analysis methodologies through tech journals and ongoing research.
  • Challenge existing thought processes and actively work in cross disciplinary groups and make a case using rich data and presentation.

***This role can be located out of any US based Verizon hub location. ***

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

What we’re looking for...

You’ll need to have:

  • Bachelor’s degree or four or more years of work experience.
  • Six or more years of relevant work experience.
  • Willingness to travel up to 25%.

Even better if you have:

  • Ph.D. in Statistics, Math, Economics, Engineering, Computer Science, Business Analytics, Data Science.
  • Master’s degree in a quantitative field or in a related field (Statistics, Mathematics, Physics, Engineering, Data Science, Operation Research, Economics etc.).
  • Eight or more years of experience in practicing machine learning and data science in business.
  • Experience in management consulting.
  • Experience in practicing machine learning and data science in business.
  • Strong experience in Big Data and Cloud technology.
  • Demonstrates complete understanding and wide application of technical procedures, principles, theories and concepts in the Telecommunications and/or Finance field. General knowledge of other related disciplines.
  • Strong communication and interpersonal influencing skills.
  • Problem solving and critical thinking capabilities.
  • Translating unstructured business problems into data science models and coming up with solutions.
  • Demonstrated experience in leading large scale data science projects and delivering from end to end.
  • Strong computing/programming skills; Proficient in at least 2 of the following (R, Python, Julia, Spark, SQL, Linux shell script).
  • Ability to adapt to quickly changing business environment and requests that come in related to upper level executive requests.
  • Accomplished researcher and expert in optimization.
  • Self-starter with can-do attitude.

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. At Verizon, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more.

COVID-19 Vaccination Requirement

Verizon requires new hires to be fully vaccinated against COVID-19. Verizon provides reasonable accommodations consistent with legal requirements (e.g., for medical or religious reasons).