Data Scientist (Machine Learning)

Location: Toronto, Ontario; hybrid work with on-site office attendance in Toronto and work from home as required by the role.

Salary: CAD 75,000–95,000 per year.

Company

hirify.global provides broadcast measurement, consumer behaviour data, and audience intelligence for broadcasters, advertisers, and agencies.

What you will do

• Conduct advanced data analytics, statistical modelling, data fusion and integration, and machine learning initiatives.
• Develop and enhance algorithms for sample design, weighting and calibration procedures, and production improvements.
• Contribute to data mining, data integration, and hybrid methodologies.
• Review statistical and machine learning models created internally or by external business partners against established research, statistical, and data science standards.
• Support cross-functional teams with analytics, presentations, and decision-making insights.
• Maintain current knowledge of statistical methods, machine learning, and AI-assisted analytics.

Requirements

• Undergraduate or graduate degree in Statistics, Data Science, Mathematics, or a related quantitative field.
• Up to 3 years of experience in a similar role or field.
• Strong expertise in applied statistics, including sampling, statistical inference, regression, imputation, model evaluation, and forecasting.
• Experience with advanced analytics, data integration, and machine learning.
• Proficiency in Python, SQL, or equivalent.
• Familiarity with reproducible analytical practices, including Git, modular development, testing, and documentation.
• Strong analytical, problem-solving, communication, and collaboration skills, including the ability to communicate findings to technical and non-technical audiences.

Nice to have

• Accredited statistician status or an Advanced Data Science certification.
• Data Science certification.
• Experience with survey, panel, weighting, audience measurement, or large-scale behavioural datasets.
• Experience with relational databases and modern cloud data warehouses or lakehouse platforms.
• Familiarity with automated data pipelines, workflow orchestration, and distributed data processing for large datasets.
• Experience implementing, deploying, and scaling analytical or machine learning models in production.
• Familiarity with natural language processing, AI-driven methodologies, Large Language Models, and synthetic population frameworks.

Culture & Benefits

• Hybrid work arrangement combining the Toronto office and work from home as required by the role.
• Health and dental benefits with employer-paid premiums, group savings, and a retirement program.
• Four weeks of paid vacation.
• Education reimbursement of up to $1,000 per year, plus continuous learning through Percipio.
• MentorMe networking and development program, leadership training, and supportive collaborative teams.
• Perkopolis employee discounts and access to community-focused initiatives.