Connor, Clark & Lunn Investment Management (CC&L) is a top-performing quant fund managing over $75 billion in financial assets. They are seeking a Quantitative Data Analyst to join their Quantitative Equity Team, focusing on leveraging data analytics and finance knowledge to enhance investment decisions and drive research capabilities.

Responsibilities

• Create processes to assess, explore, and link billions of data points
• Test structured and unstructured data sets for data quality and reliability
• Assess new data opportunities for quality and usefulness
• Evaluate your data solutions for sensibility, accuracy, and bias
• Collaborate with quantitative researchers – support alpha projects with your data expertise
• Collaborate with technology specialists – help trade off application performance and operational feasibility
• Support production deployments of your work to ensure long-term reliability
• Enable clarity of and access to your work through robust documentation and exposition
• Present findings and recommendations to key stakeholders in a clear, concise, and compelling manner

Skills

• Analytical Mindset – You think critically and creatively and are adept at balancing intuition with statistical validation
• Financial Knowledge – Desire to acquire the financial context needed to understand your stakeholders and make data decisions with impact
• 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 are able to manage and prioritize multiple ongoing projects
• Academic Training – At a minimum, an undergraduate degree in finance, mathematics, statistics, computer science, engineering, or related discipline. Completion of a relevant graduate degree is considered an asset

Benefits

• Plus a competitive performance bonus

Company Overview