Quantitative Analyst Co-op Intern

Final date to receive applications: 12/03/2026

Address: 100 King Street West

Job Family Group:
Data Analytics & Reporting

• Currently pursuing or recently completed a Master's degree or PhD in Quantitative Finance, Financial Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative discipline.
• Strong academic foundation in quantitative analysis, statistical modeling, and computational methods.

• Proficiency in Python or other programming languages used for quantitative analysis and data science.
• Experience developing and leveraging APIs to extract, integrate, and automate data workflows.
• Knowledge of quantitative modeling, process automation, and machine learning techniques.
• Experience creating data visualizations, reports, and interactive dashboards to support decision-making.
• Understanding of Bayesian statistics and their application to real-world analytical problems.
• Knowledge of financial engineering, quantitative risk analysis, or related financial modeling concepts.
• Ability to work with large and complex datasets to generate meaningful insights and recommendations.
• Strong analytical, problem-solving, and communication skills.

• Experience applying machine learning or statistical techniques within a financial services environment.
• Exposure to cloud-based analytics platforms, data engineering tools, or advanced quantitative research methods.
• Demonstrated interest in quantitative finance, financial markets, and data-driven decision making.

Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.

• Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
• Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.
• Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
• Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
• Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
• Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently on a range of complex tasks, which may include unique situations.
• Broader work or accountabilities may be assigned as needed.
• Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.

Foundational level of proficiency:

• Deep learning.
• Machine learning.
• Trust, bias and ethics.
• Creative thinking.
• Critical thinking.

Intermediate level of proficiency:

• Mathematics, statistics & operations research.
• Big data.
• Data visualization.
• Computational thinking and programming.
• Data wrangling.
• Data preprocessing.
• Complex problem solving.
• Analytical acumen.
• Creative reasoning.
• Verbal & written communication skills.
• Collaboration & team skills.
• Analytical and problem solving skills.
• Influence skills.
• Data driven decision making.
• Typically between 1-3 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
• Technical proficiency gained…