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CIBC

Quantitative Analyst/Senior Quantitative Analyst

Toronto, ON, Canada

Pay: The expected annualized base salary range for this role is $100,000 to $170,000.
Job type: Full-time
Apply by: Oct 13, 2026
Posting language: English
Posted: Sep 29, 2026

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Original job description

We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients.

At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.

To learn more about CIBC, please visit CIBC.com

What you'll be doing

The Quantitative Research Team at CIBC Global Asset Management is responsible for developing and managing systematic investment strategies across equities and fixed income, as well as improving the investment process of discretionary mandates. As a Quantitative Research Analyst, you'll contribute to the research and development of systematic active equity strategies with an AUM of over $11 Billion. You'll support the design and implementation of quantitative models, conduct empirical research, and help translate investment ideas into actionable insights. Working alongside portfolio managers and senior researchers, you'll play an important role in advancing alpha research and portfolio construction methodologies.

At CIBC we enable the work environment most optimal for you to thrive in your role. To successfully perform the work, you'll be on-site full-time.

The expected annualized base salary range for this role is $100,000 to $170,000.

The base salary is determined by a variety of factors, including the candidate’s skills, experience, and job-related knowledge, as well as geographic location and specific business needs. Our compensation philosophy supports ongoing growth and development, enabling progression within the salary range as team members advance in their roles.

In addition to base pay, compensation for this role includes participation in an annual discretionary incentive or bonus program.

We are committed to providing fair, equitable, and competitive compensation opportunities for all employees and we encourage open conversations about compensation throughout the recruitment process.

Please note, we are open to hiring at either a Quantitative Analyst or a Senior Quantitative Analyst level based on skills and experience. We encourage applications from people at different stages of their career, from recent graduates to experienced professionals.

How you'll succeed

Quantitative Research & Modelling – Contribute to the development and validation of quantitative models, including factor models and portfolio construction frameworks, to support systematic investment strategies.
Data Analysis & Insights – Analyze large datasets to identify patterns, test hypotheses, and generate actionable investment insights that support the team's research agenda.
Research Support – Collaborate with portfolio managers and senior researchers to translate investment ideas into well-documented, production-ready analytics and research findings.
Technology & Tools – Support the development and maintenance of analytical tools and codebases, primarily using Python and SQL, to enhance research workflows and investment processes.
Communication – Present research findings and analytical results clearly to diverse audiences, including Analysts, Portfolio Managers, and IT professionals, with varying levels of technical expertise.

Who you are

You're motivated by collective success. You know that teamwork can transform a good idea into a great one. You know that an inclusive team that enjoys working together can bring a vision to life.
You give meaning to data. You enjoy investigating complex problems and making sense of information. You communicate detailed information in a meaningful way.
You love to learn. You're passionate about growing your knowledge. You have a strong sense of curiosity.
You're passionate about financial markets and investing. You have a genuine interest in how markets work and are driven by the opportunity to apply quantitative methods to real-world investment challenges.
You can demonstrate experience in Python (required) and SQL (preferred), including strong knowledge of machine learning libraries (e.g., scikit-learn, PyTorch, or TensorFlow). It's an asset if you have familiarity with quantitative research tools and financial data platforms.
You have a degree in a STEM field (Computer Science/Engineering, Physics, Mathematics, Statistics, or a related discipline). A graduate degree (Master's or PhD) is preferred.

What CIBC Offers

At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential. We aspire to give you a career, rather than just a paycheck.

We work to recognize you in meaningful, personalized ways including a competitive salary, incentive pay, banking benefits, a benefits program*, defined benefit pension plan*, an employee share purchase plan, a vacation offering, wellbeing support, and MomentMakers, our social, points-based recognition program.
Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.
We cultivate a culture where you can express your ambition through initiatives like Purpose Day; a paid day off dedicated for you to use to invest in your growth and development.

*Subject to plan and program terms and conditions

What you need to know

CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact Mailbox.careers-carrieres@cibc.com
CIBC is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise.
You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit.
We may ask you to complete an attribute-based assessment and other skills test (such as simulation, coding, French proficiency).
We use artificial intelligence tools during the recruitment process. Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.

Job Location

Toronto-141 Bay, 18th Floor

Employment Type

Regular

Weekly Hours

37.5

Skills

Analytical Thinking, Decision Making, Machine Learning (ML), Professional Presentation, Python (Programming Language), Quantitative Financial Analysis, Quantitative Models, Researching, Research Reporting

Apply About employer

More about this job

Responsibilities

The Quantitative Research Analyst will develop and validate systematic investment strategies, including factor models and portfolio construction frameworks. They will also analyze large datasets to generate actionable investment insights while collaborating with portfolio managers and senior researchers.

Requirements

Candidates must have a degree in a STEM field, with a graduate degree preferred, and demonstrate experience in Python and SQL. Strong knowledge of machine learning libraries and a passion for financial markets are essential for this role.

Skills

Quantitative research
Quantitative modeling
Python
SQL
Machine learning
Factor models
Portfolio construction
Data analysis
Empirical research
Financial markets
Analytical thinking
Decision making
Professional presentation
Research reporting

Benefits

Competitive salary
Incentive pay
Banking benefits
Benefits program
Defined benefit pension plan
Employee share purchase plan
Vacation offering
Wellbeing support
MomentMakers recognition program
Purpose Day

Visa sponsorship

Not detected in the job text

Keywords

Quantitative Analyst
Systematic investment
Equities
Fixed income
Alpha research
Python
SQL
Scikit-learn
PyTorch
TensorFlow
STEM
Factor models
Portfolio construction
Data analysis
Financial data platforms
Quantitative research
Investment strategies
Machine learning
Empirical research
Asset management

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