Research & Development Associate - Open By Default

The Faculty of Information at the University of Toronto invites applications for a Research & Development Associate as part of Professor Rohan Alexander’s NSERC Alliance project, Novel Statistical and Machine Learning Algorithms for Analysis of Canadian Political Donations and Lobbying Data [ALLRP 599949-24].

The successful candidate will work closely with the grant’s industry partner, the Investigative Journalism Foundation (IJF). The successful candidate will work 15-20 hours per week from September through April. You will be paid $25/hour initially with the potential for increases as you gain experience. They must be available to work in person on either Monday or Wednesday at the IJF’s downtown Toronto office.

The deadline to apply is 5:00pm ET on Friday August 28.

The (IJF) is a nonprofit newsroom focused on public-interest journalism. We are a new kind of media outlet, built around databases on who donates to politicians across Canada, who lobbies them, and how the government spends your money.

The IJF is rapidly growing and is proud to be named one of the world’s most innovative media companies by Fast Company magazine. We were also selected for Fast Forward’s accelerator for tech non-profits, won an Anthem Award for our Open By Default database, two gold medals at the Canadian Online Publishing Awards and the Product of the Year award from LION Publishers.

As a nonprofit, nonpartisan media outlet, our primary purpose is to serve the public. We do this by publishing in-depth investigative journalism that speaks truth to power. Our databases are also used by other journalists, policymakers and academics seeking to increase transparency and strengthen Canadian democracy.

The successful candidate will handle the clerical work required by our award-winning document-collection project, Open by Default. It is a live, free repository of every access to information request fulfilled by the federal government in recent years. We track thousands of these requests every year, and each entails receiving a document from a body of government either by email or less often by post. The successful candidate will use our internal web app to process each of these receipts, and pass each included document into our system, after which it will appear on our website, freely searchable to anyone in the world. Other work requiring attention to detail, such as manually reviewing matches created by automated entity resolution algorithms, may be required.

Applicants should have an excellent attention to detail, and be thoughtful about our processes, with a particular attention to how they can be simplified and sped up. Previous work or research experience which involved handling data is an asset.

No specific technical skills are required but applicants that are comfortable with Python are especially welcome, as there will be opportunities to automate workflows which are currently manual.

You will be expected to write technical reports about the process of creating these datasets, which could ideally be submittable to academic journals and conferences. Additionally, these datasets form the basis for academic research looking at entity resolution at scale using LLMs.

Please click the Apply Now button at the top of the screen. It will ask you for your CV, all academic transcripts, and a cover letter telling us how your skills are a fit for the IJF’s mission, as well as links to up to three repositories or papers you worked on which you’re particularly proud of. With the links, please include a few sentences outlining what role you played in this project and how it best demonstrates you have the skills outlined in the “About this job” section above.