IT & Software

Quantitative Equity Product Analyst

CCLIM - Quantitative Equity

Vancouver · Metro Vancouver Regional District · Canada

We are looking for a Product Analyst to support our globally recognized quantitative investment platform. We combine quantitative research with leading-edge technology to develop differentiated algorithmic investment strategies. A culture of innovation, growth and success through collaboration and mutual respect has enabled us to deliver top tier performance for over two decades. Today, our clients entrust us with over $78+ billion USD in financial assets.

The successful candidate will contribute directly to analysis and research that translate a quantitative investment process into clear, credible content for institutional investors. This is a high-impact role for someone who combines technical depth, sound judgment, and strong communication skills.

What You Will Do

Working closely with the Quantitative Equity, Client Solutions, and Institutional Sales teams, the Product Analyst will support a broad range of activities, including:

  • Investment Content Development – Develop materials that resonate with internal/external stakeholders by clearly and succinctly relating a complex investment process to developments in markets and portfolios.
  • Business Development – Support initiatives that contribute to the long-term growth and success of the Quantitative Equity platform.
  • Cross-Team Engagement – Build strong relationships with internal stakeholders in order to improve systems, processes, and communications across teams.
  • External Presence – Represent the Quantitative Equity team in meetings with institutional clients, prospects, and consultants.

What You Bring

  • Academic background in finance, economics, statistics, mathematics, engineering, data science or a related quantitative discipline.
  • 2 – 5 years of work experience on a quantitative or systematic investment team.
  • Working understanding of factor investing frameworks, portfolio construction and optimization principles, performance attribution and risk decomposition, and empirical research methods.
  • Demonstrated ability to critically and creatively analyze large financial datasets, with a high level of attention to detail.

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Reference: WJ-291_11100054

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