What you’ll be doing... This candidate will perform analytics, create predictive models, apply machine learning techniques, and/or develop GenAI methods for high-visibility projects, as a member of a collaborative and open team that prides themselves on innovative solutions.
The data scientist will explore information from multiple sources in order to gain maximum insight and provide a competitive advantage.
The “data science” tasks may include statistical analyses, knowledge discovery, data mining, machine learning, and predictive modeling.
Responsibilities will include: -
Performing data studies of new and diverse data sources. - Conducting statistical modeling and experiment design.
Discovering “stories” told by the data and present them to peers, software developers, business analysts and business managers.
Creating and validating predictive models and advanced algorithms; train AI and machine learning algorithms.
What are we looking for: You’ll need to have:
Bachelor's degree or four or more years of work experience. - Six or more years of analytics and data science experience.
Strong knowledge of programming and pattern recognition.
Mastery of statistics, machine learning, algorithms, predictive modeling, and advanced mathematics.
Knowledge of deep learning and GenAI techniques.
Experience working with security data.
Experience working with networking data.
Experience using SQL (Structured Query Language) and other programming languages (R, C, Python) for statistical computing, graphics, and data mining.
Experience with RDBMS, columnar, and NoSQL database technologies.
Experience with Big Data and related tools such as Hadoop or Spark .
Familiarity with tools such as R, Rstudio, Python scipy and numpy, Jupyter notebook is desired.
Even better if you have one or more of the following:
Advanced Degree in one of: Computer Science, Data Science, Physics (or other science), Engineering, or Mathematics/Statistics
Strong critical thinking skills and the ability to relate them to Verizon business processes and operations.
Excellent verbal and written communication skills as well as the ability to bridge the gap between data science and business management.
Ability to collaborate with business units, IT, and data scientists across the enterprise to support descriptive and predictive analytics processes. -
Strong exploratory analysis skills and ability to think and research creatively.