Low Latency Quantitative Researcher

Tudor; New York (NY); On-site; USD 150,000 - 250,000; Full time

Job summary

Tudor’s Macro Pipeline team seeks a Quantitative Researcher to work in a low latency trading environment focused on liquid futures. You will research and implement automated signals and strategies with short to medium horizons, demanding rigorous statistical methods and efficient code paths.

Candidates typically have 3+ years of research experience, with MSc/PhD preferred in quantitative fields and strong Python/C++ skills. Salary ranges reflect location and experience.

Qualifications

• 3+ years of experience researching low latency futures signals and strategies.
• Advanced degree (MSc or PhD) from a top institution preferred.
• Strong preference for advanced degrees in Statistics, Machine Learning, Physics, Mathematics, or Engineering.

Responsibilities

• Research and implement fully automated systematic futures signals and strategies.
• Work on short to medium horizon trading models within a low-latency team.
• Handle large datasets including tick-level data with high accuracy.

Skills

Low latency research

Quantitative analysis

Python

C/C++

Statistics

Big data manipulation

Attention to detail

Entrepreneurial mindset

Education

MSc/PhD preferred

Quantitative discipline

Tools

Python

R

Julia

Job description

Tudor’s Macro Pipeline team seeks a Quantitative Researcher to work within a low latency trading team that currently researches and builds low latency trading models in the liquid futures space. The candidate’s primary responsibilities will include researching and implementing fully automated systematic futures signals and strategies with short to medium horizon. Suitable candidates will generally have at least 3 years of comparable research experience.

Requirements

• 3+ years of experience researching low latency futures signals and strategies
• An advanced degree (MSc or PhD) from a top institution is preferred
• Strong preference for advanced degrees in a quantitative field (e.g. Statistics, Machine Learning, Physics, Mathematics, or Engineering)
• Excellent understanding of probabilities, statistics and optimization
• Experience manipulating large datasets, including tick-level data
• Excellent programing skills: experience with both high-level (e.g. Python, R, Julia) and lower-level languages (e.g. C, C++) with fluency in at least one.
• High attention to detail
• Creative thinker
• Entrepreneurial spirit. Enjoys ownership of projects and takes responsibility for them

Compensation

• Annual base salary for the position is expected to be from $150,000 per year to $250,000 per year. Actual salary offered to the successful candidate will depend on various factors including, but not limited to, geographic location, work experience and credentials, and/or skill level, the salary expectations of applicable applicants, and other market conditions. Details about eligibility for bonus compensation will be finalized at the time of offer.