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Quantitative Developer

2 months ago

Boston, United States Selby Jennings Full time

Job Responsibilities:

Collaborative Development:

  • Work directly with other team members, including Quantitative Developers, Researchers, and Portfolio Managers.

Quantitative Infrastructure:

  • Develop infrastructure for alpha generation, portfolio construction, and algorithmic trading.
  • Contribute to the evolution of the firm's platform and daily alpha construction and trading.

Software Development:

  • Develop the firm's proprietary trading system, data warehouse, service-based architecture, machine learning platforms, and simulation tools.
  • Create and monitor data pipelines and strategy execution using a Directed Acyclic Graph (DAG) based scheduling system in Python.

Strategy and Technical Support:

  • Collaborate with traders and researchers to build new proprietary trading strategies and alphas.
  • Provide high-level technical and investment support.

Data Analysis and Reporting:

  • Parse and analyze new data sources (exchange data, company fundamental data, unstructured data).
  • Design tools for reporting and analyzing strategy risk, trade cost, and execution using a proprietary columnar database.

Project Ownership:

  • Own the end-to-end design, implementation, and launch of software projects spanning the mentioned technical domains.



Personal and Technical Qualifications:

Analytical and Creative:

  • Highly analytical and creative, with the ability to quickly and enthusiastically tackle new projects.

Prioritization and Multi-tasking:

  • Strong ability to prioritize and handle multiple tasks effectively.

Educational Background:

  • Possess a bachelor’s or advanced degree in computer science, engineering, statistics, or another computational or quantitative field.

Technical Proficiency:

  • Proficiency in one scripting language (Python, Bash, Perl).
  • Experience in UNIX/Linux/BSD environments.
  • Experience with relational database management systems (PostgreSQL, MySQL, etc.).
  • Proficiency in one object-oriented or lower-level language (Java/C++/C).
  1. Machine Learning and Statistical Packages:
  • Familiarity with popular machine learning, deep learning, and statistical packages (such as scikit-learn, TensorFlow, PyTorch) is recommended.