Vacancy caducado!
- Support data science partnerships and assist in verifying proposed methodologies
- Assist in the design and development of natural language processing approaches for a variety of use cases
- Create and deliver presentations and webinars explaining computational social science approaches to a variety of technical and non-technical audiences
- Promote a culture of teamwork that balances individual accomplishments and projects with broader team goals and deliverables
- Co-author peer reviewed journal articles
- Work with large teams of data analysts on innovation sprints
- Experience with natural language processing APIs in Python
- Experience with extract transfer load (ETL) protocols for unstructured data, including data cleaning, feature engineering, and exploratory data analysis (EDA)
- Understanding of statistical applications to big data
- Interest in analytic applications in global environmental change
- Bachelors degree in Computer Science, Data Science, Statistics, Information Science, or a related field
- Experience with GitHub
- Critical understanding of limitations of computational social science approaches
- Strong research skills
- Ability to communicate complex insights in a clear and precise manner
- Knowledge of Spanish, Portuguese, French, Bahasa or other languages
- Knowledge of Forest & Landscape Restoration implementation, environmental science or international development
- Masters degree in Data Science (not required)
- Applicants must have personal health insurance coverage.
- US work authorization is required for this opportunity. WRI does not sponsor interns for visas.
- This is a full-time, four-month internship with flexible start and end dates based on the students availability and need for the project.
- Some meetings are between 9am-5pm EST, however, there is flexibility regarding working hours.
- This is a remote-based internship with the option to work out of the Washington D.C. office once it reopens.
- WRI will provide a laptop for the duration of your internship.
Vacancy caducado!