The RoleWe are seeking exceptional recent graduates or final year students to join one of our Quantitative Research teams in the New York City area metro area. As a Quant Researcher you will work with other researchers and developers on various research projects, including the design of novel predictive signals and the enhancement of our algorithms for prediction, trade execution, portfolio construction, risk management, among others. You will have an opportunity to meaningfully contribute to multiple facets of running a successful quantitative trading business and help it grow and diversify. This is a high-impact role with clear ownership, mentorship, and visibility.
What You'll Do Variadic LLC, a Schonfeld partner, is a quantitative investment firm based in New York City. We are looking for recent graduates and students in their final year of study with an outstanding record of achievement who seek a role on the ground floor of a startup trading firm.
We believe we have assembled an exceptionally talented, ambitious, and hungry team. As a new hire, you will be empowered to add value from day one. New hires are immediately given full access to data and code and asked to collaborate with experienced researchers on projects across the full stack. We expect you to learn from others, develop your own process, and reinforce the culture of ambition, creativity, rigor, and hard work.
No previous financial experience is required. Max hunger is a must.
What You Need- A Bachelor's, Master's, or PhD degree in a quantitative or technical field such as statistics, mathematics, physics, electrical engineering, or computer science (ideally a recent graduate or with one year left in your academic program)
- Ability to hit the ground running on projects written in C++, JavaScript, Python, Rust, and Go, using a mix of in-house and open-source libraries.
- Willingness to learn and work on any level of the stack to drive a project to completion, from building infrastructure to manually collecting and checking data to conducting machine learning studies to managing production. No job is too small or too big.
- Intuition for maximizing expected value in decisions involving imperfect information, sophisticated adversaries, high risk, and high potential reward.
- Spider sense for missing data, outliers, time-of-day issues, statistical errors, off-by-ones, convergence failures, and software bugs; willingness to dig into the details and carefully think through corner cases.
- Hard worker. An understanding that success comes from time and effort put in by everyone on the team.
The annual base pay for this role is expected to be between $175,000 and $225,000 which will be prorated based on internship start and end date. The expected base pay range is based on information at the time this post was generated. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications and experience and level of education.
