Part-time Full Stack Developer, Social Science Prediction Platform
BITSS is looking to hire a part-time full-stack engineer to work on refining the Social Science Prediction Platform (SSPP). The engineer will work part-time (10-15 hrs/week) and start as soon as possible.
We are looking to hire a software developer with web development experience to make updates to the Social Science Prediction Platform Developed under the leadership of Principal Investigators Stefano DellaVigna (UC Berkeley), Eva Vivalt (University of Toronto), SSPP facilitates the collection and cataloging of forecasts of research results. It uses the Qualtrics API to integrate surveys programmed in Qualtrics on the SSPP interface and a relational database to connect survey responses to project objects and user data such as contact information, demographics, and preferences.
The SSPP has been built but requires updates including:
- Improving the usability and navigability of the database structure for users with admin privileges;
- Improving navigability of the project catalog;
- Improving the visual presentation of survey results, as well as automated notification to respondents;
- Ensuring the Qualtrics and Sendgrid APIs continue to function well with evolving platform features
We need a developer to work on these, as well as other minor improvements, for 10-15 hours/week possibly with a heavier load in the first 1-2 months, starting ASAP. They should be able to join two to four 1-hour virtual team calls per month.
- Python/Django skills (we use Django framework as our primary technical stack);
- Experience with DevOps (our applications are containerized using Docker and hosted on Heroku);
- Ability to build on and work with public APIs (eg, our platform calls Qualtrics APIs to work with survey data, and SendGrid APIs to enable communication with users and stakeholders. Note: we do not ask for experience with these specific APIs, but a basic understanding of how to work with other public APIs would be favorable.
- Experience with database management;
- Strong SQL and data manipulation skills; and
- Back-end development experience.
- Experience building the back-end of a database or website in which datasets are being queried, manipulated, and transferred to users;
- Front end development experience (e.g. managing user credentials, building out intuitive user interfaces);
- Some understanding of empirical economic/data science methods;
- Commitment to producing clean, well-documented code (e.g., as evidenced by public GitHub repos);
- Good communication skills, including the ability to assess and communicate technical challenges and design decisions.
How to apply
Please apply by sending your resume, GitHub profile, and links to relevant work examples to Eva Vivalt.
Applications will be reviewed on a rolling basis until May 1 or until filled.