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Wildlife Trade Data and Technology Intern - Fall 2021 (REMOTE/VIRTUAL)

Position: IFAW wildlife trade data and technology intern
(Note: We are seeking multiple interns for this role; successful candidates will be part of a team.)

Location: Virtual/remote

Application deadline: Applications will be considered on a rolling basis through August 11, 2021. Candidates are encouraged to apply early.

Term: Approximately twelve weeks with a possibility of extension. Fall internships will begin in September (start and end dates will depend upon candidates' schedules).

Eligibility: Undergraduate (2+ years completed); recent college graduate; advanced degree candidate/recipient.

Compensation: Internships are categorized as unpaid for purposes of Handshake categories, but fall interns may receive a stipend through IFAW and/or academic credit if available through their academic institutions.

About us: IFAW was founded in 1969 and its driving mission is to save individual animals, animal populations and habitats all over the world. With projects in more than 40 countries, IFAW provides hands-on assistance to animals in need, whether dogs and cats, wildlife and livestock, or animals affected by natural disasters.

Internship overview: The International Fund for Animal Welfare (IFAW) is seeking a wildlife trade data and technology intern with a strong academic record and commitment to wildlife conservation. This intern will support campaigns related to wildlife trafficking and trade, with responsibilities including data analysis, confiscation monitoring, cyber-crime research and technology-driven solutions evaluation.

The successful candidate may be responsible for assignments including but not limited to:
  • Evaluating use of e-commerce platforms for sale of wildlife parts and products
  • Evaluating state and federal wildlife confiscation data, system and trainings
  • Identifying wildlife trade data gaps and evaluate options for collecting data and streamlining enforcement
  • Interviewing enforcement officials to identify knowledge and data collection needs
  • Monitoring, compile and analyze search data related to wildlife and parts/products
  • Otherwise supporting IFAW’s campaigns and mission. 
  • Evaluating use of social media for wildlife trade, and analyzing opportunities to track demand for wildlife and wildlife products.
  • Apply technical skills related to machine learning, web scraping, and related programs/operations.

Schedule: Start and end dates for internships are flexible. The wildlife trade data and technology internship for fall 2021 will begin in September, with a preferred commitment of at least ten weeks and 12+ hours per week. 

Qualifications: Ideal candidates have an interest in computer science and/or data analysis, as well as a willingness to learn about how they can make a difference for animals by evaluating and/or developing technology-driven solutions to fight wildlife crime. This is an excellent opportunity for individuals interested in conservation, science communication, computer science/programming, coding, machine learning, and/or working at the interface of advocacy and technology.

IFAW prefers that candidates for this role meet the following requirements:
·        Strong computer science and/or data analysis experience;
·        Ability to work independently as well as in a team;
·        Ability to manage and prioritize multiple tasks and shifting priorities;
·        Completion of at least three years of undergraduate education; 
·        Availability to work remotely/virtually full- or part-time (12+ hours per week) during the internship term.


At IFAW, we aim to create and foster a workforce that reflects and contributes to the diverse, global community in which we work to improve the lives of both animals and people. We consider applicants for employment without regard to race, ethnicity, national origin, ancestry, color, age, sex, citizenship or immigration status, religion, sexual orientation, gender identity or expression, neurodiversity, disability status, family or marital status, or criminal history.