artificial intelligence (AI) analyst

TD Bank; Montreal; On-site; CAD 114,000 - 154,000; Full time

Job summary

A leading Canadian bank in Montreal is seeking an Applied Machine Learning Scientist II to develop and deploy machine learning solutions that enhance decision-making across its operations. The candidate will work with cross-functional teams, conduct rigorous model evaluations, and translate complex results to stakeholders. Ideal applicants are experienced in Python, SQL, and have a background in relevant disciplines with a strong capacity for problem-solving.

Qualifications

• 5+ years of relevant experience preferred.
• Experience in financial services or regulated environments.
• Knowledge of causal inference, anomaly detection, or agents.

Responsibilities

• Develop, deploy, and maintain predictive and generative AI models.
• Translate business problems into analytical frameworks.
• Conduct rigorous model evaluation, documentation, A/B testing, and monitoring.
• Communicate complex results to non-technical stakeholders.
• Stay current with ML research and bring innovative approaches into production.

Skills

Excellent written and verbal communication skills

Creative problem solving

Ability to translate complex technical terms

Strong internal relationship management

Education

Undergraduate degree in Science, Technology, Engineering, Math, or a related discipline

Graduate degree

Tools

Python

SQL

Azure Cloud

Azure ML Services

Job description

Title

Applied Machine Learning Scientist II (B) – TD Bank, Toronto, Ontario, Canada

Job Details

• Location: Toronto, Ontario, Canada
• Hours: 37.5 per week
• Line of Business: Analytics, Insights, & Artificial Intelligence
• Pay: $114,000 - $154,000 CAD

Job Description

We're looking for a highly motivated Applied Machine Learning Scientist to join our AI2 team. In this role, you'll drive the development and deployment of ML solutions that power data‑driven decision‑making across our Canadian Personal Banking division. You'll work closely with various teams to bring AI capabilities to life and deliver measurable business impact.

Key Accountabilities:

• Develop, deploy, and maintain predictive and generative AI models for use cases such as agentic AI, LLM‑based models, pricing, and anomaly detection.
• Translate business problems into analytical frameworks and collaborate with cross‑functional teams to define success metrics and solution approaches.
• Conduct rigorous model evaluation, documentation, A/B testing, and monitoring to ensure model performance, fairness, and stability in production.
• Communicate complex technical results to non‑technical stakeholders and provide actionable insights.
• Stay current with ML research and industry trends to bring innovative approaches into production.
• Take a lead role in scoping new models and translating business needs into analytical solutions.

Qualifications

• Excellent written and verbal communication skills.
• Comfortable and effective interacting with a wide range of business partners and stakeholders.
• Ability to develop and maintain strong internal relationships with several stakeholders.
• Ability to translate complex technical terms and concepts into easy‑to‑understand business language.
• Creative, out‑of‑the‑box thinker with strong conceptual and problem‑solving skills.
• Motivated to constantly strive to find innovative ways to enhance processes and analytical solutions.
• Capable of quickly uncovering potential drivers for model performance variation to inform lifecycle management decisions.

Technical Competencies

• Proficiency in Python and key ML libraries.
• Experience with structured and unstructured data, feature engineering, and model interpretability techniques.
• Exposure to GenAI or large language models and their practical applications.
• Hands‑on experience with model deployment and monitoring in a production environment.
• Experience with SQL, Azure Cloud and Azure ML Services is an asset.

Education & Experience

• Undergraduate degree in Science, Technology, Engineering, Math, or a modeling related discipline such as Economics or Finance.
• Graduate degree is considered an asset.
• 5+ years of relevant experience preferred.
• Experience working in financial services or regulated environments.
• Knowledge of causal inference, anomaly detection, or agents.

Benefits

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices are designed to allow colleagues to progress through the salary range over time as they advance in their role.

Advertised until: 2025-11-24