JOB REQUIREMENTS:

As a Senior Applied Machine Learning Scientist, you will lead a high-performing team of AI/ML professionals and provide technical leadership across the advanced analytics and machine learning function. You will be responsible for:

• Managing, mentoring, and developing a team of applied machine learning scientists, fostering a collaborative and innovative work environment.
• Leading the conceptualization, design, and delivery of AI/ML systems to solve complex business and enterprise-wide problems.
• Providing thought leadership and developing innovative methodologies and techniques in AI/ML.
• Collaborating with cross-functional teams including Machine Learning Engineers and research scientist, data scientists, and business stakeholders to build and implement cutting-edge analytic solutions.
• Translating business objectives into scalable technical solutions and delivering enterprise-level insights.
• Acting as a business partner to guide and prioritize strategic initiatives and analytical needs.
• Driving continuous improvement through monitoring systems, feedback loops, and trend analysis.
• Ensuring compliance with internal and external governance, risk, and regulatory requirements.
• Championing a culture of excellence, inclusion, and continuous learning within the team.

QUALIFICATION:

• Undergraduate degree required; advanced technical degree preferred (e.g., Mathematics, Physics, Engineering, Finance, Computer Science).
• Minimum of 3+ years of relevant experience, including post-graduate work in AI/ML or related fields.
• Proven experience in leading and managing technical teams, with a focus on mentorship and performance development.
• Deep expertise in AI/ML frameworks, tools, and methodologies.
• Strong strategic planning, communication, and stakeholder engagement skills.
• Extensive understanding of business operations and enterprise-level analytics.
• Experience working with large-scale data systems and advanced machine learning techniques.
• Demonstrated ability to provide specialized knowledge and guidance across multiple domains of machine learning.

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 deliver legendary customer experiences to 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 the Bank, those we serve, and the economies we support. We are guided by our vision to Be the Better Bank and our purpose to enrich the lives of our customers, communities and colleagues.
TD is deeply committed to being a leader in customer experience, that is why we believe that all colleagues, no matter where they work, are customer facing. As we build our business and deliver on our strategy, we are innovating to enhance the customer experience and build capabilities to shape the future of banking. Whether you’ve got years of banking experience or are just starting your career in financial services, we can help you realize your potential. Through regular leadership and development conversations to mentorship and training programs, we’re here to support you towards your goals. As an organization, we keep growing – and so will you.

• Managing, mentoring, and developing a team of applied machine learning scientists, fostering a collaborative and innovative work environment.
• Leading the conceptualization, design, and delivery of AI/ML systems to solve complex business and enterprise-wide problems.
• Providing thought leadership and developing innovative methodologies and techniques in AI/ML.
• Collaborating with cross-functional teams including Machine Learning Engineers and research scientist, data scientists, and business stakeholders to build and implement cutting-edge analytic solutions.
• Translating business objectives into scalable technical solutions and delivering enterprise-level insights.
• Acting as a business partner to guide and prioritize strategic initiatives and analytical needs.
• Driving continuous improvement through monitoring systems, feedback loops, and trend analysis.
• Ensuring compliance with internal and external governance, risk, and regulatory requirements.
• Championing a culture of excellence, inclusion, and continuous learning within the team