Sobre esta vaga de Quantitative Researcher – Systematic Fixed Income – Client Role na Arootah
Arootah · Híbrido · Massachusetts
About the Role
Our client, a leading global alternative investment manager, is seeking a Quantitative Researcher to join its systematic fixed income investment team. This role will focus on developing and improving quantitative trading strategies across fixed income markets, with particular emphasis on alpha research, signal development, and execution efficiency.
The successful candidate will work closely with portfolio managers, researchers, and technologists to identify new investment opportunities, improve existing strategies, and translate research into live trading applications.
Responsibilities
- Research, develop, and implement new systematic alpha signals across fixed income markets.
- Take research ideas from initial concept through testing, validation, implementation, and live trading.
- Improve strategy monetization with a focus on execution quality and transaction cost efficiency.
- Analyze trading behavior and market structure across electronic fixed income venues.
- Apply statistical, machine learning, and quantitative techniques to real-world investment problems.
- Build scalable research and trading tools to support systematic investment strategies.
- Partner with portfolio managers, researchers, and technology teams on strategy development and implementation.
- Clearly communicate research findings, methodology, and investment recommendations to internal stakeholders.
Qualifications & Preferred Experience
- 5+ years of experience in systematic fixed income research within a hedge fund, asset manager, proprietary trading firm, or sell-side trading environment.
- Strong quantitative background with a degree in Mathematics, Physics, Engineering, Econometrics, Quantitative Economics, Statistics, or a related discipline.
- Demonstrated experience researching and developing systematic investment strategies.
- Strong understanding of statistics, machine learning, and quantitative modeling.
- Experience in systematic credit is strongly preferred.
- Strong programming skills in Python, C++, or another relevant language, with the ability to develop clean and scalable research code.
- Familiarity with fixed income market structure and electronic trading venues is a plus.
- Strong written and verbal communication skills with the ability to explain complex quantitative concepts clearly.
Additional Information
We may use artificial intelligence (AI) tools to support portions of the hiring process, including resume review and candidate evaluation. These tools assist our recruiting team but do not replace human decision-making. Final hiring decisions are made by human reviewers.
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