Quantitative Researcher, PhD

As a Quantitative Researcher, you will work with a team to develop a variety of signals, models, and strategies for trading financial markets. As part of the role, you will be responsible for the design and implementation of various components of our research system, and you will evaluate their effectiveness by using rigorous statistical methods. As part of a small team with exposure to multiple areas of research, you will have the opportunity to rapidly grow your knowledge of quantitative finance.

Candidate requirements:

• Active PhD graduates or Postdocs pursuing a degree in mathematics, statistics, machine learning, physics, computer science, or other scientific discipline
• Exceptional mathematical, analytical, and problem-solving ability
• Programming proficiency in Python or C++
• Experience in solving data-intensive problems a plus
• Demonstrated ability to complete statistical or applied mathematical research a plus
• Successful participation in mathematical competitions a plus e.g., IMO, Putnam
• Prior experience in a quantitative role within a trading environment a plus
• Intellectually curious, creative, and rigorous
• Willingness to challenge assumptions and revise opinions in the face of compelling evidence
• Self-motivated and highly productive, with a strong sense of urgency and accountability
• Willing to take ownership of one’s work, working both independently and within a small team
• Meticulous attention to detail
• Ability to manage and prioritize multiple threads of work
• Able to work across disciplines
• Excellent communication and collaboration skills
• Comfortable providing and receiving actionable feedback in a collaborative team setting

The base salary for this role is anticipated to be between $150,000 and $200,000, which is based on information at the time of posting. This position may also be eligible for additional forms of compensation, such as a discretionary bonus, and benefits. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their unique skills, qualifications and relevant experience.