We’re excited and happy to start the application process for 2016. Applications are now open for Fellows, Mentors, Project Managers, and Project Partner Organizations. We expect to take around 42 fellows, 4-6 Technical Mentors, 3 Project Managers, and 12 Project Partners. We encourage everyone to read the FAQ before applying. Most questions people ask us are answered there. If you don’t find an answer to a question you have, feel free to email us.
Who are we looking for?
Fellows typically come from Computer Science, Statistics, Math, Physical Sciences, Social Sciences, and Policy backgrounds. They are mostly grad students (and some advanced undergrads and post-docs). You can read about the applicants from 2015 here.
We typically look for a mix of skills, experiences, and backgrounds. We believe that it requires a diverse set of people to solve the problems we tackle and we encourage everyone passionate about making a social impact with data science to apply. We do, however, expect a base level of computational and quantitative skills. We can’t be everything to everyone so we’ve decided to focus this program for people who have at least some computational and data analysis experience.
Typical fellows have reasonable proficiency in at least one programming language (we typically use Python) and some experience in statistics and data analysis. We are looking for a portfolio of fellows so we can create balanced cross-disciplinary teams. Typical teams consist of computer scientists, statisticians, and social scientists. Teams have access to dedicated hands-on technical mentors and project managers, as well as a larger pool of expertise within the fellowship.
Read more about what we’re looking for in the FAQs as well as our blog posts.
We look for project partner organizations that can provide us with projects that:
- Have social impact
- Can be solved using data science
- Can give us access to internal data that is necessary and relevant to solve the problem
- Have resources to devote during the summer to help the fellows understand the problem and work with them to ensure what gets delivered is relevant and useful
- Have the capacity and commitment to take what we do over the summer and use it going forwardRead more about what it takes to be a successful Data Science for Social Good Project Partner.