Vice President, Data Scientist

BMO•Toronto, ON

2d•Onsite

About The Position

We are seeking a talented and experienced Data Scientist to join our Data Cognition Team at BMO Capital Markets. As a Data Scientist, you will be responsible for developing and implementing advanced analytics and machine learning models to support algorithmic trading strategies, and drive business decisions in the front office, Investment Banking, and Corporate Banking. You will collaborate closely with business teams and other stakeholders to understand their data needs and provide insights that improve trading performance and profitability. Our Team The Data Cognition Team (DCT) at BMO Capital Markets delivers a scalable, customizable, and sustainable suite of AI-enabled products for multiple business units. Leveraging cutting-edge data and analytics technologies, we solve complex business challenges and drive strategic transformation across Investment Banking, Global Markets, and other divisions.

Requirements

Ph.D. in Computer Science, Mathematics, Physics, or a related quantitative field (focus on finance, economics, or operations research preferred).
Minimum 3 years of experience in data science or machine learning; experience in capital markets is a strong asset.
Proficiency in statistical modeling, time series analysis, and machine learning frameworks.
Strong programming skills (Python preferred) and experience with cloud technologies.
Familiarity with financial tools such as Bloomberg, FactSet, and Thomson Reuters is a plus.
Excellent problem-solving skills and ability to formulate hypotheses and learn from data.
Strong communication skills for effective collaboration with technical and business stakeholders.
Team-oriented, adaptable, and detail-focused with a results-driven mindset.

Nice To Haves

Experience with Generative AI and advanced ML techniques.
Knowledge of investment banking concepts, trading strategies, and financial data formats.
Familiarity with MLOps tools and practices for model deployment and monitoring.

Responsibilities

Develop and implement advanced analytics and machine learning models using techniques such as Generative AI, Deep Learning, and Reinforcement Learning.
Build predictive models for algorithmic trading across asset classes including Equities, Fixed Income, Commodities, and Foreign Exchange.
Collaborate with trading desks, investment banking teams, and corporate banking stakeholders to identify opportunities and optimize strategies.
Research and experiment with new machine learning techniques, including time series analysis, to improve trading performance and profitability.
Design and maintain reproducible machine learning pipelines for production environments.
Analyze large datasets to extract insights and support strategic decision-making.
Communicate complex technical concepts to non-technical stakeholders and present findings to senior management.
Visualize complex data clearly and concisely for business consumption.