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Data Science Intern (Social Media Analysis)

FireEye, Inc.

Data Science Intern (Social Media Analysis)

New York, NY
  • Responsibilities

    Job Description



    The FireEye Data Science team is seeking a motivated intern candidate to uncover malicious and manipulative patterns in large volumes of digital data. This intern will need to be able to clearly communicate the progress of the project and any motivations for making research decisions. They should be willing and able to participate in daily discussions with remote team members, balance greenfield research with short time budgets, and quickly pivot between generating new hypotheses and testing them via well-documented experiments. They should also be comfortable encapsulating their ideas within Jupyter notebooks, GitHub repositories, and in scientific writing. The ideal candidate will be open-minded, able to provide and receive feedback on advanced topics in cybersecurity and data science, and able to hit the ground running as an independent thinker and tinkerer.


    • Conduct research into the tactics, techniques, and procedures being employed by adversaries over social and digital channels.
    • Perform a literature review on state of the art methods being used to detect, analyze, and contextualize these operations.
    • Will utilize in-house, open source, and other relevant data sources to develop a data-driven detection capability, and demonstrate its performance on real-world, streaming holdout data.
    • Experiments will be documented, presented, and evaluated regularly, and a capstone presentation and white paper will be prepared for both internal and external dissemination at the conclusion of the internship.
  • Qualifications



    • Experience in applying a wide variety of unsupervised, semi-supervised, and supervised machine learning techniques.
    • An understanding of machine learning processes and workflows, and experience with basic statistical analysis of social media data.
    • Strong skills in Python development and use of machine learning packages.
    • Experience with Linux command line and Jupyter notebooks.
    • Ability to document and explain technical details clearly and concisely.
    • Strong written and verbal communication skills.
    • Ability to work as part of a remote team.
    • Must be a continuing college or university student in good standing at an accredited institution pursuing a Master's or PhD degree

    Additional Information

    All your information will be kept confidential according to EEO guidelines.