Building a job matching system that works for people with disabilities - ON-1185

Genre de projet: Innovation
Discipline(s) souhaitée(s): Informatique, Sciences mathématiques, Statistiques / études actuarielles, Affaires, Sciences sociales et humaines
Entreprise: EnabledTalent
Durée du projet: 4 à 6 mois
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): ON, Canada
Nombre de postes: 2
Niveau de scolarité désiré: CollègeÉtudes de premier cycle/baccalauréatMaîtriseDoctoratRecherche postdoctoraleNouvelle diplômée/nouveau diplômé
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: No

Au sujet de l’entreprise: 

Enabled Talent is a Toronto-based technology company focused on employment for persons with disabilities. We build tools that help
job seekers with disabilities connect to employers, plan workplace accommodations, and succeed in the long term. The employment gap for people with disabilities in Canada is well documented. Over 6 million working-age Canadians live with a disability, yet their employment rate is roughly 20 points below the national average. In most cases this is not a question of ability. It is a question of systems. Most hiring tools were not built with accessibility in mind. We are fixing that. The platform serves job seekers with disabilities, employers working to meet accessibility requirements, and workforce support
organizations helping people transition into employment. We work with post-secondary institutions, incubators, and workforce development organizations across Ontario.

Veuillez décrire le projet.: 

Enabled Talent is building a job matching system designed from the ground up for people with disabilities. Most platforms match candidates to jobs based on skills and experience alone. Our system also accounts for accommodation needs, workplace accessibility, and employer readiness. To do this well, we need to research and validate the matching logic before it goes into production. This internship covers three areas of work.

Matching model research
The intern will research and test different approaches to matching candidates to job opportunities when accessibility variables are part of the equation. This includes comparing model types, testing them against real employment data, and checking whether the outputs treat all disability groups fairly.

Employer scoring framework
Before a match can be made, we need a reliable way to assess how accessible an employer actually is. The intern will design a scoring method based on factors like physical workspace, accommodation history, HR readiness, and workplace culture. They will build the data collection tools and test whether the scores hold up across different employer types.

Outcome tracking
Good matches should lead to long-term employment, not just placement. The intern will design a methodology to track whether people placed through the platform are staying in their jobs and advancing. This data will be used to improve the matching logic over time.

Expertise ou compétences exigées: 

Required
-Statistical modelling or machine learning, with experience in classification or matching problems
-Proficiency in Python or R for data analysis
-Strong research skills including experimental design and quantitative methods
-Understanding of how to identify and address bias in computational systems

Preferred
-Familiarity with labour market data or workforce systems
-Knowledge of Canadian accessibility standards such as AODA
-Experience designing surveys or structured data collection tools

Asset
-Lived experience with disability, not required but valued in this research context