Senior Data Science Engineer (AI)

Location: Remote in Canada, with EST working hours

Salary: CAD 130,000–155,000 annual base salary, with potential bonus awards

Company

hirify.global provides AI-powered financial risk intelligence through its hirify.global AI platform, which analyzes financial transactions for finance and audit professionals.

What you will do

• Apply deep knowledge of scoring logic, risk indicators, control points, and ensemble methodologies.
• Configure and tune existing models and ensembles based on customer data and control objectives.
• Assess data quality, structure, volume, and feasibility for proposed configurations.
• Investigate model behaviour and underperformance, distinguishing data quality issues, configuration problems, and product limitations.
• Partner with Product, Engineering, and AI/ML teams on model changes, capability gaps, and technically grounded escalations.
• Explain model outputs and configuration boundaries to finance, audit, compliance, Success Engineering, and Delivery Services stakeholders.

Requirements

• 5+ years of applied experience in data science, analytics engineering, or a closely related technical discipline.
• Working knowledge of statistical and machine learning techniques for anomaly and risk detection, including scoring models, ensemble methods, and outlier detection.
• Strong SQL, Python, and data literacy, with the ability to investigate customer datasets independently.
• Experience working directly with enterprise customers on technical questions in support, technical account management, implementation, or applied customer-facing data science.
• Ability to explain technical model behaviour to finance, audit, and compliance stakeholders and collaborate as a peer with Engineering and AI/ML teams.
• Must be based in Canada and work primarily in EST. Employment is contingent on meeting the requirements for a full background check.

Nice to have

• Experience in audit, internal controls, financial risk, or fraud analytics.
• Familiarity with explainability and interpretability in regulated or audit-facing environments.
• Experience creating FAQs, playbooks, or training materials for internal technical teams.
• Post-implementation optimization experience or a background in ML engineering or applied statistics.

Culture & Benefits

• Flexible remote or hybrid work options.
• Competitive compensation, equity, and comprehensive health and wellness benefits.
• Professional development opportunities and flexible time off.
• Company-matched retirement plans.
• Four company-wide digital detox days annually.