What you'll be doing...
HQ Service Performance Team is seeking a lead data analyst to execute complex analytical studies on how network metrics correlate mathematically with each other and correlate to the customer experience. As a member of this highly technical team, the candidate will act independently and be responsible for fulfilling complex business requirements related to Service Performance (including, but not limited to RAN/ EPC / Benchmarking) objectives.
As the lead data analyst on the Service Performance team, you will be responsible for creating algorithms and processing data to provide additional value across multiple data sets. This analysis will be used to ensure a continued exceptional customer experience, drive field teams to focus on the most impactful areas, automate and improve process, and keep Verizon as the undisputed best network from a 3rd party perspective. The selected employee will be responsible for understanding the team's big data objectives, how they contribute to Verizon's success, and then investigating and implementing data science technologies that best support the mission.
The candidate will need advanced analytic skills to find relationships, models, and statistical associations between massive data sets. This task is above the level or experience of a standard Computer Science degree and requires that the individual be specialized in algorithms, statistics, data engineering and machine learning. The Data Scientist will setup and execute these studies from hypothesis to study conclusion in a practical academic fashion.
Work with team to understand use cases and available data.
Perform exploratory data analysis to understand the relationships between Verizon data set.
Develop and implement big data, machine learning, and artificial intelligence capabilities that can predict and optimize key quantities and events in the Verizon network.
Analyze various data to interpret competitive results to understand competitive decisions and areas for opportunity.
Utilize strong presentation skills to promote and explain projects in terms of their value to the business as well as value to recipients.
Work with peer Data Analytics teams throughout Verizon to share best practices and add additional value to analysis.
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.
Practical experience with programming languages (such as R and Python).
Willingness to travel.
Even better if you have:
Master's in Data Science or in a related discipline.
Four or more years of experience developing and implementing machine learning and artificial intelligence algorithms.
Experience in two of the following, proficient in all other tasks: Statistical analytics, Data Visualization, GIS, AI, and Machine Learning, Big Data methods, linear and nonlinear mathematical analysis.
Ability to work in a team and independently on multiple high priority projects.
Ability to manage multiple high-visibility, complex technical projects.
Experience in the areas of machine learning, neural networks, statistical learning, and exploratory data analysis.
Experience in Data Visualization tools such as Tableau.
Ability to gain expertise in the above fields as projects dictates.
Strong problem solving skills.
Strong written and oral communication skills.
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.