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- Full-time
3–5 years of experience within the financial services/securities industry, with specific knowledge of wealth operations processes.

Applied Machine Learning Scientist II

Toronto, ON, Canada

$81,600 - $115,200 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually. · Full-time

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Job details

Pay: $81,600 - $115,200 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.
Job type: Full-time
Apply by: Oct 20, 2026
Experience: 5+ years of relevant experience.
Posting language: English
Posted: Oct 6, 2026

Original job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$81,600 - $115,200 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

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 have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Department Overview

Applied Machine Learning Science is a specialized field within advanced analytics that brings deep expertise in Artificial Intelligence (AI) / Machine Learning (ML) to drive innovation and improvements in business practices. This area is focused on developing and applying a broad set of evolving advanced AI/ML techniques to solve business problems. It includes gathering, analyzing, and modeling a wide range of data, applying mathematical models/techniques and tools, and utilizing software engineering best practices to develop and implement the solutions.

Key Responsibilities

Provide technical expertise, develop, and implement state-of-the-art machine learning models relevant to products for personal banking: marketing, risk management, and strategy optimization.

Analyze large and complex - structured and unstructured - datasets (scaling to petabytes), deploy deep learning techniques including large language models to develop solutions.

Perform feature engineering and selection from raw data to enhance model accuracy and interpretability.

Conduct research, support development, prepare and deliver presentations and communicate progress, plan and risk related to projects to stakeholders.

Actively manage relationships within and across various business lines, corporate and/or control functions and ensure alignment with enterprise and/or regulatory requirements.

Write/create and maintain appropriate documentation.

Ensure respective programs/policies/practices are well managed, meets business needs, complies with internal and external requirements, and aligns with business priorities.

Lead / facilitate and/or implement actions / remediation plans to address performance / risk /governance issues.

Keep abreast of emerging issues, trends, and evolving regulatory requirements and assess potential impacts.

Maintain a culture of risk management and control, supported by effective processes in alignment with risk appetite.

Act as a brand ambassador for your business area/function and the bank, both internally and/or externally

Job Requirements

Advanced university degree (Master's and PhD) in STEM - statistics, computer science, mathematics, physics, engineering etc.)

5+ years of relevant experience.

Proven experience in development and deployment of machine learning models in production.

Solid understanding of machine learning, deep learning, large language models, and traditional statistical methodologies.

Hands-on coding experience with Python, PySpark, PyTorch and SQL are required.

Experience with cloud platforms, such as Azure.

Knowledge of AML regulations and financial crime risks is desirable.

Strong problem-solving skills and good writing skills as well as ability to communicate complex concepts to non-technical audiences.

Experience in graph-based machine learning and LLMs, especially transformers, is highly desirable

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.

Colleague Development

If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you’re passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.

Interview Process
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.

Accommodation
Your accessibility is important to us. Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.

We look forward to hearing from you!

Language Requirement (Quebec only):

Sans Objet

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More about this job

Responsibilities

Develop and implement state-of-the-art machine learning models to support personal banking products including marketing, risk management, and strategy optimization. Analyze large, complex datasets and utilize deep learning techniques to drive innovation and business improvements.

Requirements

Requires an advanced university degree (Master's or PhD) in a STEM field and at least 5 years of relevant experience. Candidates must possess strong hands-on coding skills in Python, PySpark, PyTorch, and SQL, along with experience in cloud platforms like Azure.

Skills

Machine Learning
Deep Learning
Large Language Models
Python
PySpark
PyTorch
SQL
Azure
Statistical Modeling
Feature Engineering
Data Analysis
Risk Management
Strategy Optimization
Graph-based Machine Learning
Transformers

Benefits

Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs

Visa sponsorship

Not detected in the job text

Keywords

Applied Machine Learning
Artificial Intelligence
Advanced Analytics
STEM
Statistics
Computer Science
Mathematics
Physics
Engineering
Production Deployment
Structured Data
Unstructured Data
Petabytes
Model Accuracy
Interpretability
Stakeholder Communication
Regulatory Requirements
Risk Appetite
Brand Ambassador
AML Regulations
Financial Crime Risks

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