Applied Machine Learning Scientist II

Location: Remote; Toronto, Ontario, Canada

Salary: $125,500–$154,000 CAD annually; the posted pay reflects a temporary market premium reassessed annually.

Company

hirify.global is a large financial institution serving banking customers and businesses in Canada, the United States, and other markets.

What you will do

• Develop and implement state-of-the-art machine learning models for personal banking marketing, risk management, and strategy optimization.
• Analyze structured and unstructured datasets at petabyte scale and apply deep learning, including large language models.
• Perform feature engineering and selection to improve model accuracy and interpretability.
• Research, develop documentation, prepare presentations, and communicate project progress, plans, and risks to stakeholders.
• Manage relationships across business lines and control functions while aligning solutions with enterprise and regulatory requirements.
• Address performance, risk, and governance issues through remediation plans and maintain effective risk-management controls.

Requirements

• Advanced university degree, such as a Master's or Ph.D., in STEM, including statistics, computer science, mathematics, physics, or engineering.
• 5+ years of relevant experience.
• Experience developing and deploying machine learning models for marketing use cases, including customer propensity, next best action, churn prediction, customer lifetime value, or audience targeting, with demonstrated business impact.
• Exposure to financial services, banking, retail, telecommunications, or digital marketing ecosystems, including customer segmentation, campaign management, and personalization platforms.
• Proven experience developing and deploying machine learning models in production.
• Strong understanding of machine learning, deep learning, large language models, and traditional statistical methodologies.
• Hands-on coding experience with Python, PySpark, PyTorch, and SQL, including cloud platforms and MLOps practices for building, monitoring, and productionizing machine learning solutions.
• Strong problem-solving and writing skills, with the ability to communicate complex concepts to non-technical audiences.
• Ability to keep current with emerging issues, trends, and evolving regulatory requirements.

Nice to have

• Experience with generative AI, large language models, recommendation systems, graph analytics, or causal inference applied to marketing and customer experience problems.

Culture & Benefits

• Base salary, variable compensation, health and well-being benefits, savings and retirement programs, paid time off, banking benefits, and discounts.
• Career development opportunities, regular development and performance conversations, mentoring programs, and access to an online learning platform.
• Training and onboarding sessions are provided.
• Respectful workplace with diverse perspectives and fair growth opportunities.
• Accessibility accommodations are available throughout the interview process.

Hiring process

• Candidates of interest will be contacted to schedule an interview.
• Interview outcomes are communicated by email or phone where possible.