Description

JOB STATEMENT:

Guardian Capital Group Limited (Guardian) is a global investment management company servicing institutional, retail and private clients through its subsidiaries. As of September 30, 2025, Guardian had C$166.6 billion of total client assets while managing a proprietary investment portfolio with a fair market value of C$1.3 billion. Founded in 1962, Guardian’s reputation for steady growth, long-term relationships and its core values of authenticity, integrity, stability and trustworthiness have been key to its success over six decades. Its Common and Class A shares are listed on the Toronto Stock Exchange as GCG and GCG.A, respectively. To learn more about Guardian, visit www.guardiancapital.com.

Our asset management division, Guardian Capital LP, is the manager and portfolio manager of the Guardian Capital Funds and Guardian Capital ETFs, with capabilities that span a range of asset classes, geographic regions and specialty mandates. Guardian Capital LP manages portfolios for institutional clients such as defined benefit and defined contribution pension plans, insurance companies, foundations, endowments and investment funds.

The primary responsibility of the Data Science Intern is to leverage knowledge in machine learning techniques and AI tools to assist in the development of the company’s proprietary R&D infrastructure and risk analytics for fixed income investment.

Working closely with the Fixed Income Team in an exciting live market environment, the candidate will work alongside our Senior Analysts and Portfolio Managers to develop models and tools to augment existing investment risk analytics and improve the systematic processes for fixed income asset allocation and security selection.

ESSENTIAL FUNCTIONS:

Quantitative Research (approx. 2/3 of work hours):

  • Working on projects that enhance the automation of investment management processes and optimization of portfolio construction and security selection
  • Participating in quantitative research assignments including collecting, cleaning and transforming data, building and testing machine learning models, etc.

Credit and ESG related analysis (approx. 1/3 of work hours)

  • Updating proprietary ESG scoring models and reports, assisting in analyzing corporate bond issuers from an ESG perspective

QUALIFICATIONS:

  • Currently enrolled in quantitative undergraduate or graduate degree program (e.g. math, statistics, data science, engineering or finance program) with the expectation of graduating in winter 2026 or spring/summer 2027
  • Have a strong understanding of software development and an interest in finance and investment analysis
  • Strong coding skills and experience in Python, SQL and prompt engineering
  • Knowledge and project experience in Machine Learning/Deep Learning/NLP/LLM preferred
  • Excellent written and verbal communication skills with ability to explain complex issues
  • Professional work ethic, ability to manage tasks and maintain confidentiality
  • Ability to work independently as well as within a team environment

COMPENSATION:

  • Hourly rate of $25-$30/hour, based on experience