Data Science Researcher Intern
FireEye - Reston VA

Internship Category: Paid

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  • Position Title: Data Science Researcher Intern

    Location: Reston, VA

    The Company:

    FireEye has invented a purpose-built, virtual machine-based security platform that provides real-time threat protection to enterprises and governments worldwide against the next generation of cyber attacks. These highly sophisticated cyber attacks easily circumvent traditional signature-based defenses, such as next-generation firewalls, IPS, anti-virus, and gateways. The FireEye Threat Prevention Platform provides real-time, dynamic threat protection without the use of signatures to protect an organization across the primary threat vectors and across the different stages of an attack life cycle. The core of the FireEye platform is a virtual execution engine, complemented by dynamic threat intelligence, to identify and block cyber attacks in real time. FireEye has over 4,000 customers across 67 countries, including more than 650 of the Forbes Global 2000.

    The Role:

    FireEyes Innovation & Custom Engineering (ICE) Data Science team has been conducting research on deep learning models for malware classification of Windows executables. This research has successfully demonstrated that these models are effective at detecting malware by just examining the bytes in a file (e.g., with no pre-processing of the file). FireEye would now like to see whether the success in detecting malicious Windows executables translates to additional file types (PDF, DOC, RTF, etc.). The potential benefit of this research would be additional detection capabilities without requiring subject matter experts to help define features associated with the new file types.

    Working as a part of the FireEye ICE-Data Science team, this role will perform, record, and present data science research with the following goals:
    • Experiment with and run a Convolutional Neural Network (CNN) for use with malicious documents.
    • Build CNN for various types of lure documents PDFs, DOCs, RTFs, etc.
    • Evaluate and record results of experimentation against FireEye data.
    • Assemble results into a paper we publish at a conference/workshop.

    Responsibilities:

    • Perform research on application of CNN classifier various forensic artifacts
    • Provide weekly updates to ICE-DS team
    • Engage in team meetings, discussions, and presentations
    • Record repeatable experiments in FireEye github repository and produce detailed documentation of findings
    • Present research on bi-weekly basis and prepare final presentation at end of internship

    Requirements:

    • Experience in applying a wide variety of unsupervised, semi-supervised, and supervised machine learning techniques
    • An understanding of malware detection, and experience with basic static and dynamic analysis of binaries
    • Strong skills in Python development and use of machine learning packages
    • Experience with Linux command line and Jupyter Notebooks
    • Must be currently enrolled in an accredited University and returning to school in the Fall to be eligible

    Additional Qualifications:

    • 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
    FireEye is an Equal Opportunity Employer: All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status, or on the basis of disability. Click here to view the full EEO/AA statement.
  • LI-AL
Position Title: Data Science Researcher Intern

Location: Reston, VA

The Company:

FireEye has invented a purpose-built, virtual machine-based security platform that provides real-time threat protection to enterprises and governments worldwide against the next generation of cyber attacks. These highly sophisticated cyber attacks easily circumvent traditional signature-based defenses, such as next-generation firewalls, IPS, anti-virus, and gateways. The FireEye Threat Prevention Platform provides real-time, dynamic threat protection without the use of signatures to protect an organization across the primary threat vectors and across the different stages of an attack life cycle. The core of the FireEye platform is a virtual execution engine, complemented by dynamic threat intelligence, to identify and block cyber attacks in real time. FireEye has over 4,000 customers across 67 countries, including more than 650 of the Forbes Global 2000.

The Role:

FireEyes Innovation & Custom Engineering (ICE) Data Science team has been conducting research on deep learning models for malware classification of Windows executables. This research has successfully demonstrated that these models are effective at detecting malware by just examining the bytes in a file (e.g., with no pre-processing of the file). FireEye would now like to see whether the success in detecting malicious Windows executables translates to additional file types (PDF, DOC, RTF, etc.). The potential benefit of this research would be additional detection capabilities without requiring subject matter experts to help define features associated with the new file types.

Working as a part of the FireEye ICE-Data Science team, this role will perform, record, and present data science research with the following goals:
  • Experiment with and run a Convolutional Neural Network (CNN) for use with malicious documents.
  • Build CNN for various types of lure documents PDFs, DOCs, RTFs, etc.
  • Evaluate and record results of experimentation against FireEye data.
  • Assemble results into a paper we publish at a conference/workshop.

Responsibilities:

  • Perform research on application of CNN classifier various forensic artifacts
  • Provide weekly updates to ICE-DS team
  • Engage in team meetings, discussions, and presentations
  • Record repeatable experiments in FireEye github repository and produce detailed documentation of findings
  • Present research on bi-weekly basis and prepare final presentation at end of internship

Requirements:

  • Experience in applying a wide variety of unsupervised, semi-supervised, and supervised machine learning techniques
  • An understanding of malware detection, and experience with basic static and dynamic analysis of binaries
  • Strong skills in Python development and use of machine learning packages
  • Experience with Linux command line and Jupyter Notebooks
  • Must be currently enrolled in an accredited University and returning to school in the Fall to be eligible

Additional Qualifications:

  • 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
FireEye is an Equal Opportunity Employer: All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status, or on the basis of disability. Click here to view the full EEO/AA statement.
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