Staff Data Scientist

Description

Staff Data Scientist role on a 12 month contract, hybrid, based at 33 Dundas Street West in Toronto. Application deadline: 11/14/2026.

Job family group: Data Analytics & Reporting.

The team builds machine learning and AI models that turn large amounts of structured and unstructured data into insights the business can act on. Work moves from prototype to production, and the solutions are meant to be robust enough for enterprise use.

The role sits between data science and software engineering, so the person should be strong in both, with hands-on experience putting ML systems into production at scale.

Responsibilities

• Use machine learning, deep learning and AI methods to build models that analyze large structured and unstructured datasets.
• Work with data scientists, engineers and analytics staff to tune, productionize and scale analytical solutions into enterprise-grade products.
• Lead as a technical mentor, coaching team members on software engineering and MLOps practices.
• Raise code quality through design reviews and code reviews.
• Help the team reach a high technical standard.

Requirements

• Deep knowledge of machine learning and deep learning algorithms, covering model development, validation, optimization, deployment and monitoring.
• Experience building, deploying and maintaining production ML solutions at scale.
• Experience developing ML models and assessing new technologies and tools to deliver data-driven solutions for business stakeholders.
• Solid software engineering foundations, including advanced Python, algorithms and data structures.
• Experience reviewing code and promoting coding standards, sound software design and engineering best practices.
• Hands-on use of Git, GitHub and version control in collaborative development workflows.
• Clear communication and the ability to collaborate across data science, engineering, product and business teams.
• Nice to have: experience with AWS, SageMaker Unified Studio, lakehouse architectures, PySpark, feature stores and MLOps platforms.
• Nice to have: experience in banking, fintech or other highly regulated industries.
• Nice to have: technical leadership or people management, including mentoring and leading cross-functional teams.
• Nice to have: a Master's or PhD in Computer Science, Machine Learning, Statistics, Mathematics or a related field.
• Nice to have: research experience and publications at top-tier venues such as NeurIPS, ICML, ICLR, KDD or equivalent.
• Nice to have: typically 5-7 years of relevant experience and a post-secondary degree in a related field, or an equivalent mix of education and experience.

Conditions

Salary range: $80,000.00 to $175,000.00, salaried. This is the company's pay range and pay type for the role.

Actual pay depends on location, skills, experience, education and qualifications, and may include a commission structure. For commission roles, the listed figure is the expected first-year target.

Part-time pay is pro-rated to the hours regularly worked.

Total compensation varies by pay type and may include performance incentives, discretionary bonuses and other perks and rewards.

The company is committed to an inclusive, accessible workplace, and accommodations are available on request during the selection process.

Benefits

• Health insurance.
• Tuition reimbursement.
• Accident and life insurance.
• Retirement savings plans.