Quantitative Equity Analyst – Reliability Engineering

Quantitative Equity Analyst – Reliability Engineering

Connor, Clark & Lunn Investment Management Ltd.

Vancouver, BC

We are looking for a Quantitative Equity Analyst to join our Quantitative Equity Team! We are a high‑performance team embedded in a top‑performing quant fund that manages over $75 billion in financial assets. We are dedicated to the mission‑critical operation of our investment engine—a well‑tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging finance skills and cutting‑edge technology, we ensure data quality, continuous process improvement, and operational excellence.

As a core member of our team, you will collaborate with investment experts to tackle challenging analytical problems, be accountable to ensure accurate and timely trade generation, and drive operational innovation. Based in West Coast Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment engine and overall success.

This is an exciting full‑time role for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges.

You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process.

After training, you will transition to a specialized role using data science and process engineering skillsets to accelerate the Quantitative Equities Team’s various investment functions. Your specialized role may involve building, scaling, managing and/or analyzing our quantitative model, portfolios, data assets and optimizers.

You will receive coaching and mentorship from senior members of the team and will be supported as you grow your career steadily over time.

The team you will be joining is our Investment Process Management (IPM) group within our Quantitative Equities Team. IPM plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical to the team’s ability to develop systematic investment insights and generate daily trades to capture these insights in portfolios.

The opportunity within the IPM group allows ambitious individuals to drive their career growth within IPM, or across the other functions of the Quantitative Equities Team in Research, Portfolio Construction, or Trading.

• Design, implement and test production processes to run the alpha and risk, portfolio optimisation and market implementation processes.
• Design robust, high performance and effective process orchestration.
• Monitor production health and respond to critical issues in a timely manner.
• Effectively communicate real‑time production issues to portfolio managers, traders and researchers.
• Identify computational bottlenecks and improve run speeds in production systems.
• Collaborate with investment teams to ensure their process needs are being met.
• Find and evaluate areas for process improvements.
• Assess and evaluate data quality of production processes.
• Maintain process repos, clean code and tools within production processes.

• Construct and run algorithms to explore and assess data effectively.
• Validate structured and unstructured data sets for data quality.
• Design and test data loaders and security matching processes and specifications.
• Perform data analysis and provide data expertise to support researcher’s projects.
• Facilitate production machine learning operational pipelines with effective and timely auditing and analysis.
• Enable accessibility and clarity within our data assets through robust documentation and data scrubbing.
• Develop robust methodologies for assessing and analysing data in time‑critical production environments.
• Respond to and mitigate vendor data issues effectively in a production setting.
• Collaborate with cross‑functional teams to integrate traditional and alternative data into existing analytical…