Quantitative Analyst, Fall 2026 (Co-op/Internship) - 4 Months

BMO•Toronto, ON

About The Position

The Quantitative Analyst uses advanced analytical algorithms and technologies, including machine learning, deep learning, and artificial intelligence, to mine and analyze large sets of structured and unstructured data to obtain insights. This role involves designing and constructing new processes for modeling data, developing predictive models, and leveraging big data technology to create solutions that drive smarter business decisions, improve customer experience, and enhance productivity. The analyst collaborates with other data and analytics professionals to optimize, refine, and scale analysis into mature analytics solutions. Key responsibilities include playing an active role in data display and advancing innovative data strategies to understand consumer trends and address business problems. The position also involves data mining and extracting usable data to assess the feasibility of AI/ML solutions, conducting large-scale analysis to discover patterns and trends, and providing data-driven recommendations to business leaders to maintain market competitiveness. The analyst will develop prediction systems and machine learning algorithms, investigate new technologies and tools for innovative data solutions, and collaborate with product teams and partners for data-driven decision making, business planning, and future roadmaps. The focus is primarily on a business/group within BMO, with potential for broader, enterprise-wide impact. The role requires exercising judgment to identify, diagnose, and solve complex problems independently, and taking measured risks while adhering to the bank's Risk Management Framework, Risk Culture, and approved Risk Appetite.

Requirements

Masters level education is required
Coding experience in Python/SQL is required
API to extract data/or automate
Modeling/automation & machine learning experience required
Dashboard building
Bayesian Stats
Financial engineering
Foundational level of proficiency in Deep learning
Foundational level of proficiency in Machine learning
Foundational level of proficiency in Trust, bias and ethics
Foundational level of proficiency in Creative thinking
Foundational level of proficiency in Critical thinking
Intermediate level of proficiency in Mathematics, statistics & operations research
Intermediate level of proficiency in Big data
Intermediate level of proficiency in Data visualization
Intermediate level of proficiency in Computational thinking and programming
Intermediate level of proficiency in Data wrangling
Intermediate level of proficiency in Data preprocessing
Intermediate level of proficiency in Complex problem solving
Intermediate level of proficiency in Analytical acumen
Intermediate level of proficiency in Creative reasoning
Intermediate level of proficiency in Verbal & written communication skills
Intermediate level of proficiency in Collaboration & team skills
Intermediate level of proficiency in Analytical and problem solving skills
Intermediate level of proficiency in Influence skills
Intermediate level of proficiency in Data driven decision making
Typically between 4 - 6 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience
Technical proficiency gained through education and/or business experience

Responsibilities

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 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.
Exercises judgment to identify, diagnose, and solve problems within given rules.
Works independently on a range of complex tasks, which may include unique situations.
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.