Investigative Journalism Foundation
Research & Development Associate, Investigative Journalism Foundation
Location: Toronto (remote work is fine, but you must be based in Ontario)
Salary: PhD students: $35/hour. Masters students: $25-35/hour. Undergraduate students: $19-25/hour.
Employment: 1) 35 hours/week from May to August with possibility for extension or 2) part-time for 12 months (we will allocate, but please specify your preferred option in your cover letter)
Deadline: Please apply ASAP. Applications will be evaluated, and positions filled, on a rolling basis. Last application will be accepted March 31 at 5 pm ET or when all positions are filled.
About the Investigative Journalism Foundation
The Investigative Journalism Foundation 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.
Launched in 2023, the IJF is rapidly growing and proud to have been selected for Fast Forward’s 2024 Accelerator for tech non-profits. We’re also delighted to have been a finalist for Startup of The Year from the Institute for Nonprofit News and New Business of The Year from LION Publishers. We also won an Anthem Award for our Open By Default database, a Digital Publishing Award in the Data Journalism category 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
This is a position that starts in May 2025. It has a strong possibility of renewal. Ideal candidates include Ph.D. students in computer science, statistics, information, economics, political science, or related disciplines. Exceptional masters or undergraduate students are also encouraged to apply.
Please note: This position can only be filled by current University of Toronto students or individuals who have graduated in the past two years. It is funded via a five-year Natural Sciences and Engineering Research Council of Canada grant co-led by U of T Professors Rohan Alexander, Jesse Gronsbell and Shurui Zhou entitled Novel Statistical and Machine Learning Algorithms for Analysis of Canadian Political Donations and Lobbying Data.
The successful candidate will play a key role in developing a framework for automated data validation using LLMs to automatically generate expectations and validation tests for data. Unlike standard data validation workflows, ours will enable more rapid and comprehensive data validation through LLM assistance.
These methods will produce immediate value by revealing hidden patterns in the IJF’s public interest datasets, but will also produce long-term value as we will package our methods as open-source software that others can use on any data. Both projects will empower the public, policymakers, and academic researchers.
What you’ll do at the IJF:
- Experiment with cutting edge workflows for data validation testing (we’ve used Python’s Great Expectations and Pydantic packages in the past).
- Develop performance tests for data validation with IJF data. This will include evaluating data validation against performance tests and expert-derived data validation tests.
- Work with professors to conceptualize, conduct, and author academic publications by taking ownership of self-contained research questions within the larger project. To start, we’ll want you to build on this academic paper: Evaluating the Decency and Consistency of Data Validation Tests Generated by LLMs.
- Work with developers to take the data validation tools and integrate them into the back and front-end of the IJF’s website.
- Work with reporters to convert raw data into stories that hold the powerful accountable and make Canada a better place.
- Assist the professors in guiding and mentoring undergraduate research assistants working on the project.
We’re looking for someone with:
- Excellent writing skills. Familiarity with academic writing conventions is good. Experience writing academic papers, particularly in statistics or computer science, is better.
- The ability to code and work with large quantities of data. Experience with Python, R or other scripting languages used for data analysis. Database management skills, including SQL will be good too.
- The ability to work in a reproducible way. For instance, writing clean, commented, code and comfortable using platforms such as GitHub.
- Excitement about working at a data journalism-focused nonprofit. We integrate things like topic modelling, machine learning and natural language processing in our editorial process. You don’t need to know how to do any of these things, but if you do, tell us in your cover letter.
- Comfort with interdisciplinarity. This job requires working with statisticians, political scientists, software developers and journalists on complex questions that straddle disciplines.
- Familiarity with LLMs including systematic development and ablation of various natural language prompts, including formatting and syntax; zero-, one-, and few-shot learning; sensitivity to semantic changes.
- We are primarily looking for PhD students. However, exceptional masters and undergraduate students are encouraged to apply.
Not sure you’re qualified for this job? Please apply anyway. We’re looking for talented people who share our passion for making Canada a better place. Experience matters less than a desire to learn and grow. We’re committed to building an inclusive environment.
How to apply:
Please fill out the form on this website. It will ask for a cover letter telling us how your skills are a fit for this role, and a copy of your CV. Your CV should include a link to your GitHub if you have one.
We’re looking forward to hearing from you.
— The IJF team
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