QUALIFICATIONS

• Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance, or computer science).
• Graduate degree preferred or progressive project work experience.
• 3+ years of relevant experience; higher degree education and research tenure can be counted.
• Strong organizational skills with the ability to work in a fast-paced environment and manage multiple deadlines and priorities.
• Ability to effectively work in teams across the bank with multiple stakeholders and to influence and align others.
• Strong risk acumen – challenges the status quo and proactively manages risks.
• Ability to work in ambiguity and simplify complex issues.
• Strong work ethic and ability to execute with speed.

TECHNICAL SKILLS

• Proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and PySpark) and SQL (writing complex queries, stored procedures, and data extraction).
• Hands-on experience with machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and causal inference.
• Familiarity with generative AI (GenAI), large language models (LLMs), and statistical inferencing.
• Experience building, training, and deploying machine learning models, including model pipelines, feature engineering, hyperparameter tuning, and model explainability.
• Experience with cloud-based data and AI/ML platforms (e.g., Azure, AWS, or GCP), including deploying and managing models in production environments.
• Proficiency in tools like Power BI, Tableau, or similar platforms to create impactful visualizations and dashboards.

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.

• Use a wide range of programming languages (e.g., Python) and data science techniques for extracting and preparing data, applying statistics and advanced analytics, along with business acumen to extract insights or build analytics solutions.
• Design, develop, and deploy machine learning models, including supervised and unsupervised learning, reinforcement learning, and generative AI (e.g., large language models). Build and maintain model pipelines to ensure scalability and efficiency.
• Visualize insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
• Work in partnership with various functional areas to provide day-to-day support and delivery of analytics.
• Support in the production of reports on the oversight of monitoring over TD’s branch colleagues’ adherence to policy and procedures as needed.
• Identify new analytical trends and data needs to improve repeatable analytic solutions.
• Employ techniques and theories drawn from mathematics and statistics to extract knowledge or insights from structured and unstructured data.
• Enhance business strategies by leveraging analytics and insights to foster strategic thinking and guide informed decisions.
• Translate up-to-date information into continuous improvement activities that enhance performance.
• 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.
• Participate fully as a member of the team, supporting a positive work environment that promotes service to the business, quality, innovation, and teamwork.