Please only apply to one job posting. In the application questions below, you’ll have the opportunity to indicate if you’re interested in multiple offices and/or roles. Please do not submit multiple applications for different positions/offices!

This role is directed at graduates seeking a 2025 start date. For 2026 start dates please take a look at our internships.

Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability.

 Qualifications

• You are a full-time undergraduate or masters student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2025
• Experience programming in Python and/or C++
• Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
• A passion for applying quantitative models and technology toward solving real-world problems
• Brilliant analytical and problem-solving skills
• Ability to work creatively and independently on long-term technical problems

Profile

• You are capable of working independently as well as part of a team
• You can analyze and fix problems efficiently
• You learn quickly and apply new skills effectively

Annual base salary range of $175,000 to $250,000. Pay (base and bonus) may vary depending on job-related skills and experience. A sign-on and discretionary performance bonus will be provided as part of the total compensation package, in addition to company-paid medical and/or other benefits.