Quantitative Developer, Systematic Trading

Quantitative Developer, Systematic Trading

Please direct all resume submissions to QuantTalentUS@mlp.com and reference REQ-13172 in the subject.

Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.

A small, collaborative, entrepreneurial and highly pedigreed systematic investment team is seeking an experienced developer to join in building critical trading infrastructure. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.

Location

Flexible in the US with a strong preference for Palm Beach, FL

Principal Responsibilities

Partner closely with Quant Researchers to implement data pipeline using High Performance Computing technologies.
Engage in development of order execution stack.
Assist in designing and maintaining automation tools for the systematic trading infrastructure.
Perform data analysis and generate automated reports in assisting systematic strategy design.
Stay current on state-of-the-art technologies and tools, computing environments, and academic research in areas of machine learning and finance.
Collaborate with the PM and the trading group in an open, collaborative environment, engaging with the investment process.

Preferred Technical Skills

Advanced degree in Computer Science, Engineering, Applied Mathematics, Statistics or related STEM field. Bachelor degree with relevant years of experience considered.
Excellent in Python, specifically knowledgeable in Pandas and Numpy, scientific computing library stack. Proficiency in C++ definitely a plus.
Working knowledge of git, linux command line tools, and associated devops automation.
Knowledge of HPC, computational grid tech-stack a plus: distributed file systems, parallel processing frameworks.
Demonstrate excellent communication, analytical and quantitative skills.

Preferred Experience

3-6 years of work experience.
Open to candidates coming from both tech and the finance industry.
Quick learner with deep thinking abilities and openness to doing research in the future.
Experience transforming and visualizing data, attention to detail and nose for data-scrutiny.