Capital Markets Fall 2019 Co-op, Algorithmic and Quantitative Trading Opportunities (min. 8 months)
Toronto, ON
Algorithmic and Quantitative Trading Student Opportunities

At RBC, AI and machine learning are powering the next generation of electronic trading solutions for our clients. Data scientists on our Toronto trading floor are at the centre of this effort, applying cutting-edge algorithms and hardware to torrents of high-frequency transaction data. Working collaboratively within global cross-functional teams of traders, developers, and relationship managers, your technical skills, creativity, and entrepreneurial mindset will enable you to see things differently and drive initiatives to deliver value and insights for the world’s largest money managers.

Global Equities – Algorithmic & Quantitative Trading

The Algorithmic & Quantitative Trading group is seeking students with creative and structured thought processes who have an interest in the fast-paced world of electronic trading. Past accomplishments have included RBC's patented smart order routing technology known as THOR (as mentioned in "Flash Boys") and Canada’s first artificial intelligence trading network.

Global Markets Artificial Intelligence Lab

The nature of finance is changing, and RBC Capital Markets is looking to recruit the next generation of AI engineers to build cutting edge electronic trading algorithms. Joining the Global Markets AI Lab as an AI Engineer or Data Scientist, you will have the opportunity to work with cutting-edge machine learning research, build systems to support a first of its kind AI-based trading algorithm, and lead projects that have real-world and significant impact for the firm.

What will you do?

Research, create, and implement quantitative trading strategies using optimization and cutting-edge machine-learning techniques
Apply critical thinking and problem solving skills to expand already-existing algorithms that trade millions of shares and thousands of times a second
Develop key support systems to help train, and explain the actions of our reinforcement learning algorithms
Analyze market data to investigate previously unexplored structural research areas
Be challenged to think critically within a collaborative team working on Canada’s largest trade floor

Core Competencies:
Creative and novel problem solving approach
Programming experience in statistical modeling languages (Python, R, or MATLAB preferred)
Machine learning experience (reinforcement learning experience a plus)
Proficiency in optimization and Bayesian statistics
An interest in Canadian/US equity markets
Solid background in mathematics, statistics and software development
Maturity to independently carry out research projects
Strong desire to be part of a team and excellent communication skills
Experience in finance is not required