Python Quantitative Developer

Location New York
Discipline: Financial Technology
Job type: Permanent
Contact name: Lewis Piper

Contact email:
Job ref: 1698
Published: 8 months ago
Quantitative Developer 
170k-250k USD
New York

Our client is a prominent global hedge fund that places a strong emphasis on harnessing technological advancements and data-driven strategies to achieve superior returns in the market.

Job Description: Quantitative Developer

The position involves being part of a cohesive systematic global macro team situated in New York. The team specializes in employing advanced statistical and machine learning methodologies to develop short-term strategies within futures, swaps, and FX markets.

​​​​​​​Key Responsibilities:
  • Collaborate closely with the Senior Portfolio Manager to create data engineering and predictive tools for systematic trading.
  • Assist in the design, coding, and maintenance of tools essential to the systematic trading infrastructure.
  • Manage the Software Development Life Cycle (SDLC), which encompasses unit testing and Continuous Integration/Continuous Deployment (CI/CD) infrastructure.
  • Author, schedule, and oversee the workflow for the team.
Desired Technical Proficiency:
  • Proficiency in Python, with an expert-level command.
  • Demonstrated familiarity with distributed computing technologies, including Kubernetes, and event-based architectures.
  • Comprehensive understanding of fixed income, swaps, futures, and FX.
  • Possession of a Bachelor's, Master’s, or PhD degree in Computer Science, Engineering, Applied Mathematics, Statistics, or a related STEM field from a reputable university.
  • Excellent communication skills, along with a strong analytical and quantitative acumen.
Preferred Experience:
  • Prior involvement in trading platform development, encompassing work involving high-frequency databases.
  • A background of 2-5 years in finance or technology.
  • Over 3 years of hands-on experience with Python programming.
Highly Regarded Relevant Background:
  • Exposure to a systematic trading environment or comparable experience on the sell-side.
  • Familiarity with user interfaces, including CSS frameworks like Bootstrap or Materialize, as well as visualization frameworks like D3.js.
  • Knowledge of machine learning and statistical techniques, in addition to associated libraries.
  • A collaborative mindset, coupled with a keen willingness to contribute and assist others.
  • Strong critical thinking abilities and a knack for generating innovative concepts.