Data Scientist, Investment Data

Overview

Connor, Clark & Lunn Investment Management is hiring a Data Scientist for its Quantitative Equity Team in Vancouver. The team operates within a high-performing quant fund overseeing more than $75 billion in financial assets and focuses on the core data operations that support investment research and trade generation. The role centers on turning complex and messy data into dependable assets that can be used for research and alpha generation.

This is a full-time position for someone who wants to deepen their understanding of quantitative equity investing while solving data, mathematical, and technology challenges. You will begin with structured training on the investment process and the broader quantitative equity business, then move into specialized work using data science, machine learning, AI, and process engineering to improve data preparation and modelling.

The team values mentorship, collaboration, and long-term growth. You will work closely with investment experts, data specialists, and technology partners in a supportive environment aimed at building useful data products for research and strengthening investment outcomes.

Responsibilities

• Improve and refine practical named entity recognition methods and build knowledge graphs at scale.
• Design algorithms and processes to locate, connect, analyze, and evaluate billions of data points.
• Assess structured and unstructured datasets for accuracy, quality, and trustworthiness.
• Partner with quantitative researchers to support alpha-related projects through data expertise.
• Work with technology teams to balance application performance with operational practicality.
• Help deploy solutions into production and support their reliability over time.
• Create clear documentation and explanatory materials so the work is easy to understand and use.
• Share insights and recommendations with stakeholders in a concise and compelling way.

Requirements

• Strong analytical thinking with the ability to combine intuition and statistical validation.
• Hands-on experience building, validating, and improving machine learning and AI models on large datasets.
• Comfort solving ambiguous data problems that involve technical complexity and business trade-offs.
• Interest in learning financial concepts and applying them to stakeholder needs and data decisions.
• Self-driven approach with accountability for quality and timeliness.
• Collaborative communication style and the ability to explain technical ideas clearly.
• Ability to manage and prioritize several active projects at once.
• At least an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or a related field; a relevant graduate degree is an advantage.

Additional Information

The company welcomes applicants across experience levels, including interns, recent graduates, and seasoned professionals.

The stated base pay is $125,000 to $200,000 per year, and a competitive performance bonus is also offered. Final compensation will depend on experience and qualifications.

Applicants are expected to submit a resume, cover letter, and transcript.

The employer is committed to diversity, equity, and inclusion and provides equal opportunity regardless of gender, ethnicity, religion, sexual orientation or expression, disability, or age.

Applications are reviewed by the hiring team, and automated AI screening is not used in the selection process at this time.