Associate Political Data Science Jobs in Toronto, ON

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 Thursday August 27.

About the Investigative Journalism Foundation

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.

About this job

The successful candidate will work with the IJF’s technical team on one of several software projects aimed at cleaning, joining and analyzing Canadian political data. These projects include:

1. Entity Resolution: resolve many separate references like “Rogers Comms” into one Rogers entity
2. Municipal Decisions: scrape and parse procedural documents from Canada’s 130 largest municipalities
3. Identifying Local News: crawl the web to identify items from a news outlet local to a given geographical area

We are interested in applicants who have experience developing software with collaborators, ideally by some prior work experience and in a production environment. However, if you have good fundamentals and clear communication, we want to hear from you. 

Applicants should be comfortable with Python and its data science ecosystem. Applicants should also have experience with managing repositories on GitHub. The IJF has two technical specialties, web scraping and NLP, and experience in either is an asset. These technologies include: 

• Concurrent Python with asyncio
• HTTP, HTML parsing, and browser automation via Playwright
• Deep Learning with PyTorch
• LLM invocation and prompt-engineering with the openai package

Beyond these, familiarity with any of the rest of our stack is also a plus, including:

• PostgreSQL
• Pydantic, SQLAlchemy and FastAPI
• Docker
• AWS S3 and ECS
• NextJS and React

This NSERC funded-project uses these datasets as the basis of research articles. Success in this role means establishing a production-pipeline that results in useable datasets. You would be expected to write technical notes to support research using this dataset or indeed about the creation of the dataset itself that could be submitted to academic journals or conferences.

How to apply

Please fill out the form here https://theijf.applytojobs.ca/technical/50215. 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.