What you’ll be doing...

Join our IT Application Security team responsible for advanced data analytics for cyber threat hunting. You will function as a Data Scientist providing strategic direction for the Application Security Team developing architecture for Big Data Cybersecurity projects. You will develop complex data models using machine learning and AI functions. You will drive the adoption of Big Data analytics based on evaluated industry and corporate requirements.

You will be responsible for researching, designing and prototyping scalable models based on machine learning, data mining, and statistical modeling to solve key Security and Fraud problems. You will build tools and support structures needed to analyze data, pares data elements, feature selection and feature engineering in conjunction with best practices. You will work with development and security teams to ensure models can be implemented as part of a delivered solution replicable across many clients. You will lead in developing fraud use cases to identity and catalog user behavior to finger print traffic in real time.

  • Presenting findings to stakeholders to drive improvements and solutions from concept through to delivery.
  • Keeping up-to-date on the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand.
  • Leading application teams to develop risk KPIs and identifies critical events to be sent for cross channel analysis.
  • Working with other security teams to develop Fraud Cases to detect and mitigate customer account compromise.
  • Performing real time stream analysis to alert and mitigate malicious HTLM traffic flows.
  • Conducting application cross channel analysis to detect and alert on multithread attacks.
  • Researching and investigating new fraud attacks against Verizon.

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.
  • Experience developing advanced analytic queries using Spark, MapR, Splunk or Elk.

Even better if you have:

  • Master’s degree in Computer Science, Cybersecurity, Mathematics or equivalent.
  • Understanding of cybersecurity, networking traffic analysis, intrusion detection, offensive security, data science, big data analyses, predictive analytics and computer science.
  • Ability to script in multiple languages like Python (including ETL: HDFS, Hive, Nifi, Scoop, PIG, Oozie, HDP2.6, etc.).
  • Experience working with Kafka, Elastic Search, Kibana in real time solutions.
  • Demonstrated history of leading and delivering analytics models and solutions.
  • Demonstrated strong skills in software prototyping and engineering with expertise in applicable programming and analytics languages (Python, R, C/C++) and open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations.
  • Demonstrated ability to propose novel solutions to problems, performing experiments to show feasibility of their solutions and working to refine the solutions into a real-world context.
  • Ability to perform statistical analysis and inference, data modeling, clustering and predictive analysis independently.
  • Experience normalizing and parsing large data sets.
  • Experience with Big Data AWS Cloud.

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.