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

BMO•Toronto, ON

5d•CA$67,200 - CA$124,200•Onsite

About The Position

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.

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

Mine and analyze large sets of structured and unstructured data to obtain insights using advanced analytical algorithms and technologies.
Design and construct new processes for modeling data.
Develop predictive models and leverage big data technology to design solutions.
Collaborate with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.
Play an active role in the futuristic display of data, and advancement of innovative data strategies.
Use data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions.
Conduct large-scale analysis of information to discover patterns and trends.
Provide recommendations and advice for business leaders.
Develop prediction systems and machine learning algorithms.
Investigate additional technologies and tools for developing innovative data solutions.
Collaborate with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.