Selby Jennings is working with a hedge fund that is a elite milti-manager platform that invests capital with Internal and Partner portfolio managers, primarily in quantitative, fundamental equity, and tactical trading strategies. With over 30 years of experience, they have successfully capitalized on market inefficiencies and developed proprietary technology and risk analytics to expand our portfolio exposure globally across various asset classes and products.
They are looking for a skilled Quantitative Developer to join their dynamic and newly established quantitative investment team, which operates within a revenue-generating unit. As part of this team, you will engage in researching and implementing strategies across various disciplines, including systematic fundamental analysis, sector-specific approaches, and statistical arbitrage. Your responsibilities will span multiple greenfield technology projects deployed on cloud-based environments, focusing on areas such as machine learning, data warehousing, analytics engineering, ETL & ELT, containerization, and infrastructure-as-code
What you'll do:
- Collaborate with the team to construct infrastructure supporting trading pipelines in a production environment.
- Design and deploy research tools while contributing to the architectural design of our greenfield research and trading buildout.
- Develop infrastructure capable of supporting cloud-based solutions and distributed computing, contributing to the creation of a cutting-edge computational environment.
- Play a meaningful role in all aspects of running a successful quantitative trading business within a supportive and collaborative team environment.
Requirements:
- Bachelor's degree in a STEM field from top 25 University.
- Proficiency in Python.
- Excellent communication and teamwork skills.
- Experience with cloud-based environments (AWS/Google Cloud/Azure) and distributed/parallel programming.
- Ability to translate research ideas into efficient and scalable tooling.
- Aptitude for transforming mathematical concepts and data analysis into clean, high-quality software.
- Strong desire to grow as an engineer within a research and trading team.
Preferred qualifications:
- Previous experience with machine learning.
- Prior experience in the financial industry.
- Familiarity with collaborating with researchers/analysts as end users.
Culture:
They foster a collaborative and teamwork-oriented environment where ideas are encouraged and shared at all levels. They prioritize the development and advancement of our talent through interactions, learning opportunities, and meaningful contributions.
Compensation:
$150,000 - 250,000 base and $300,000 - 500,000 Total.
