Quantitative Research Intern (Financial markets) - QC-259

Desired discipline(s): Engineering - other, Engineering, Computer science, Mathematical Sciences, Finance, Mathematics, Operations research, Statistics / Actuarial sciences
Company: Squarepoint
Project Length: 4 to 6 months
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Montreal, QC, Canada; Canada; Canada
No. of positions: 1+

About the company: 

Squarepoint is a global investment management firm that utilizes a diversified portfolio of systematic and quantitative strategies across financial markets that seeks to achieve high quality, uncorrelated returns for our clients. We have deep expertise in trading, technology and operations and attribute our success to rigorous scientific research. As a technology and data-driven firm, we design and build our own cutting-edge systems, from high performance trading platforms to large scale data analysis and compute farms. With main investment offices in New York, London and Singapore, we emphasize true, global collaboration by aligning our investment, technology and operations teams functionally around the world.

Please describe the project.: 


  • Research and implement strategies within the firm’s automated trading framework.
  • Analyze large data sets using advanced statistical methods to identify trading opportunities.
  • Develop a strong understanding of market structure of various exchanges and asset classes.

Typical Day: Primary focus throughout the day is on researching and implementing trading ideas.

Apply here: http://www.squarepoint-capital.com/job#804482

Required expertise/skills: 

  • Quantitative background - includes degrees in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics.
  • Programming proficiency with at least one major programming or scripting language (e.g. C++, Java, Python).
  • Strong communication skills and ability to work well with colleagues across multiple regions.
  • Ability to work well under pressure.