Quantitative Equity Data Analyst

FortWood Capital LP

  • About the Role
  • Application Form
  • About Connor, Clark & Lunn I…

We are looking for a Data Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $111 billion 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 data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research.

Do you love the idea of integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in data. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success.

What You Will Do

This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of data, investment, 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 analytics and data science skillsets to enable the Quantitative Equity Team’s research. Your role will involve identifying and assessing brand new data, data exploration, and proposing robust ways to integrate data products from many sources.

You will be supported with coaching and mentorship from senior members of the team, and we will create the conditions for you to grow your career steadily over time. This is an opportunity for ambitious individuals

to drive their career growth in data.

Role

While we take the approach of tailoring the career path to individual strengths, we expect successful candidates for this role to develop excellence in the following tasks:

  • 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.

What You Bring

  • 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.

We welcome applications from candidates with different levels of experience, including interns, new graduates, and experienced professionals. The base salary range for full-time roles is $125,000 – $200,000 annually plus a competitive performance bonus. Compensation will be determined based on experience and qualifications.

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

Thank you for applying.

Your application has been received - we appreciate the time and effort you put into submitting your application. Our Talent Acquisition team is currently reviewing all applications, and will be in touch if your background aligns with what we’re looking for in this role. In the meantime, feel free to explore our careers page to learn more about life at Connor, Clark & Lunn Financial Group! - Working at CC&L | CC&L Financial Group Ltd. Warm Regards, The Talent Acquisition Team

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Connor, Clark & Lunn Investment Management is a global institutional asset management firm established in 1982 and based in Vancouver, Canada. Our strong, stable team of investment professionals manages a broad range of investment solutions that includes traditional mandates such as developed and emerging market equities and fixed income, as well as alternative strategies such as portable alpha, market neutral and absolute return. When you join our team, you’ll have the opportunity to make a real impact through meaningful work. It’s a place where you can grow your skills and contribute to our business.

Connor, Clark & Lunn Investment Management is an affiliate of the Connor, Clark & Lunn Financial Group Ltd. (CC&L Financial Group), one of the largest private, independently held asset management firms in Canada. CC&L Financial Group and its diverse family of affiliates collectively manage over $222 billion in financial assets. Together, we provide a broad range of distinct and independently managed traditional and alternative investment products and services to our clients.

Learn more by exploring our website: www.cclinvest.com/

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