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.
This role offers an excellent opportunity to apply your technical skills to real world challenges and see your work positively impact colleague and customer experience. You will be expected to work with multiple business partners to advance the use of Machine Learning and AI TD.
Key Accountabilities
Develop, deploy, and maintain Predictive and Generative AI models for use cases such as:
Agentic AI, LLM-based models, Pricing, 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 of new models – translate business needs into analytical solution.
Job Requirements
Communication & relationship skills:
Excellent written and verbal communication.
Comfortable and effective when interacting with 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.
Strategic Thinking & Judgment:
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 life-cycle 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 modeling related discipline such as Economics or Finance.
Graduate degree is considered an asset.
5+ years of relevant experience preferred.
Nice to Have:
Experience working in financial services or regulated environments
Familiarity with causal inference, anomaly detection or agents.
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.
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