Mid-Frequency Quant Researcher: Alpha Generation & Trading

Hudson River Trading; New York (NY); On-site; USD 175,000 - 300,000; Full time

Benefits offered by this job

Discretionary bonuses

Competitive benefits package

Job summary

Hudson River Trading seeks quantitative researchers to develop mid-frequency systematic trading strategies using rigorous statistical methods on large datasets. You will implement trading models based on novel predictions of market behavior and work with world-class research and trading infrastructure.

Successful candidates will contribute to alpha generation, portfolio construction/optimization and trade execution algorithms, while writing code to productionalize ideas.

Qualifications

• 3+ years of prior work experience in stat-arb required.
• Degree in a quantitative or technical discipline (e.g. statistics, computer science, physics, mathematics, economics).
• Exceptional academic credentials and strong numerical ability.
• Experience researching with large noisy real-world datasets and attention to detail.
• Strong work ethic and ability to thrive in a fast-paced environment.
• Proficiency in Python for data analysis and machine learning; C++ experience is a plus.

Responsibilities

• Develop mid-frequency systematic trading strategies.
• Contribute to alpha generation, portfolio construction/optimization and trade execution algorithms.
• Prototype and productionalize research ideas via code; collaborate with other researchers.

Skills

Stat-arb experience

Python for data analysis

Numerical programming

C++ proficiency

Attention to detail

Education

Degree in quantitative/technical discipline

Exceptional academic credentials

Tools

Python

C++

Job description

Hudson River Trading seeks quantitative researchers to develop mid-frequency systematic trading strategies using rigorous statistical methods on large datasets. You will implement trading models based on novel predictions of market behavior and work with world-class research and trading infrastructure.

Successful candidates will contribute to alpha generation, portfolio construction/optimization and trade execution algorithms, while writing code to productionalize ideas.