Valens Labs Spring Intern, Valens Global (Washington, DC)


Valens Global is known for its rigorous research and straightforward analysis. Valens helps governments, private companies, and non-governmental organizations understand, visualize, and address the challenges posed by violent non-state actors (VNSAs), the adversarial nation-states that sponsor them, and other emerging threats. Valens seeks to raise the standard for the field through rigorous research and advanced methods of analysis within an adaptive organization that consistently and confidently produces innovative solutions.

Valens Global is seeking an intern whose primary duties will involve qualitative coding for a big-data project. The project, conducted in collaboration with Valens Global’s sister company, Valens Labs, uses an internally developed platform designed to harness the power of artificial intelligence to project future risks and trends related to terrorism and other forms of sub-state violence. The project will yield new insights into the question of when, where, and how sub-state violence will occur. Thus, it will allow clients with an international presence to rationalize their defenses against violence.

The intern will be responsible for conducting extensive open-source research on the dynamics of violent non-state actors’ attacks carried out around the world. The intern’s role in the project involves identifying and compiling violent attacks for the intern’s assigned geographic region(s), as well as coding various open-source indicators related to those attacks.

Candidates should be prepared to contribute immediately, and should be able to transition swiftly into the coding process. Candidates should have familiarity on topics related to violent non-state actors such as jihadist militancy and transnational criminal organizations. Preference will be given to candidates who have experience in qualitative coding, as well as network and content analysis. This project is research-intensive, requiring the intern to consult open-source material, primary and secondary sources, and social media data.

The intern is expected to work 20-25 hours per week, and will receive a compensation that is competitive with other policy internships. Valens Global’s head office is located in Rosslyn, VA. The ideal candidate is highly organized, detail-oriented, and is able to stay on top of deadlines and produce quality work within tight time constraints. Throughout the internship, the intern can expect to build skills in research methodologies, open-source intelligence analysis, and qualitative coding.


Candidates should demonstrate strong interest in the study of violent non-state actors. Applicants would ideally have prior research experience, and have the ability to think creatively about complex problems. Dedication, focus, and enthusiasm are valued. Other minimum requirements include:

  • Possess strong critical thinking and analytical skills.
  • Must have unparalleled attention to detail.
  • Able to commit to a minimum of 20 hours per week.
  • Must be eligible to work in the United States.
  • Presently working toward, or recently obtained, a Bachelor’s Degree from an accredited university.
  • Experience with qualitative coding and/or social network analysis.
  • The ability to conduct research in Spanish is strongly preferred.


  • Cover letter. Note: Please highlight any qualitative coding experience in your cover letter.
  • Resume or CV.
  • At least two, and preferably three, references. Note: We are not looking for letters of recommendation, but rather people willing to serve as a reference for your qualifications who would be happy to talk to us about your candidacy.
  • One brief writing sample (5 pages or less) that displays the applicant’s ability to convey complicated information concisely and clearly.
  • Unofficial transcript copy.

Prospective candidates will be asked to complete a skills test prior to hiring.

Please send all application materials in a single PDF to

Application deadline: October 27

For more information, click here.

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