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CCLIM - Quantitative Equity

Quantitative Equity Analyst Process Engineering

Vancouver, BC, Canada

Pay: The annual base salary range is $155,000 – $350,000.
Posting language: English
Posted: Oct 2, 2026

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Original job description

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 quantitative equity fund that manages over $78+ billion USD 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'll 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.

What You Will Do

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.

You will then continue to a specialized role utilizing 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 be supported with coaching and mentorship from senior members of the team.

We are creating the conditions for you to grow your career steadily over time.

Investment Process Management

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 in 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.

While we take the approach of tailoring the career path for the individual, we have found our functions to cover two main overarching technical skillsets:

Process and Reliability Engineering

Design, implement and test production processes to run the alpha and risk, portfolio optimization 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 bottle necks 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.

Data Science

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 analyzing 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 frameworks and decision-making processes.
Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner.

What You Bring

Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation.
Financial Knowledge – You possess a thorough understanding of (or strong desire to learn) key drivers of business success, including financial theory, economic models, and corporate financial statements.
Self-Starter – You are motivated and willing to take personal accountability for quality and timeliness of work.
Collaborative Approach – You thrive in a collaborative environment and value shared success. You proactively solicit and provide input and excel at communicating complex and technical concepts.
Time Management – You have the ability to manage and prioritize multiple ongoing projects and daily responsibilities.
Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of CFA or relevant graduate degree is considered an asset.
Industry Experience – You have a passion for quantitative finance, equity investment, data science or related fields.

We welcome applications from candidates with a range of experience, including new graduates and experienced professionals. The annual base salary range is $155,000 – $350,000. Our compensation and benefits package includes a substantial variable year-end bonus, RRSP contribution matching, health benefits, and family-building benefits.

As a private organization owned by active leaders, our structure provides opportunities for exceptional contributors to participate in profit sharing and, over time, potentially become equity owners of the firm.

To apply for this position, please submit your resume, cover letter, and academic transcript.

Learn more by exploring our website: www.cclimq.com

We are committed to providing an inclusive, accessible recruitment and selection process. We welcome and encourage applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process. Please contact talentacquisition@cclgroup.com if you require accommodation.

AI may be used to support certain stages of our screening & recruitment process. These tools support, but do not replace, human judgment and decision-making.

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More about this job

Responsibilities

You will design, implement, and maintain robust process management systems and data pipelines to support quantitative investment strategies. Additionally, you will collaborate with investment experts to analyze data, optimize performance, and ensure the reliability of production trade generation.

Requirements

Candidates must hold at least an undergraduate degree in finance, mathematics, statistics, computer science, or engineering. Strong analytical skills, a passion for quantitative finance, and the ability to work collaboratively in a technical environment are essential.

Skills

Quantitative finance
Data science
Process engineering
Financial theory
Economic models
Corporate financial statements
Statistical validation
Process orchestration
Machine learning
Data analysis
Portfolio optimization
Risk management
Clean code
Critical thinking
Time management

Benefits

Variable year-end bonus
RRSP contribution matching
Health benefits
Family-building benefits
Profit sharing

Visa sponsorship

Not detected in the job text

Keywords

Quantitative Equity
Investment Management
Process Engineering
Data Science
Reliability Engineering
Alpha
Risk Management
Portfolio Construction
Machine Learning
Data Quality
Financial Modeling
CFA
Quantitative Finance
Process Orchestration
Computational Efficiency
Investment Engine
Systematic Investment
Data Loaders
Security Matching
Production Health
Alternative Data
Analytical Frameworks
Profit Sharing
Equity Ownership
Mentorship

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