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McGregor Boyall

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Python Quant Developer – Systematic Equities & Credit

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Summary

Python developer on a small cross-functional engineering team supporting systematic trading in equities and credit. Day to day: build and own production Python applications, research tooling and financial data pipelines for quant researchers and traders, focusing on performance, data quality and reliability. Core stack: Python with NumPy, Pandas and SciPy.

Overview

In this role you will join a small, cross-functional engineering team supporting systematic trading in equities and credit. You will develop and maintain production Python applications, research tooling, and data pipelines used by researchers and traders. You will translate research needs into scalable software and own applications end-to-end. You will tackle performance, data quality, and reliability challenges while promoting solid engineering practices. This role offers proximity to systematic trading and the chance to broaden exposure to other strategies.

Responsibilities
  • Develop and maintain production Python applications, research tooling and financial data pipelines used by quantitative researchers and traders
  • Collaborate with investment teams to translate research requirements into reliable software
  • Own applications throughout their lifecycle (development, testing, deployment and improvements)
  • Address performance, data quality and reliability challenges and promote good development practices
  • Contribute to a culture of maintainable, scalable software in a production environment
  • Work closely with cross-functional teams to support systematic trading strategies across equities and credit
Key requirements
  • Strong Python development experience in financial markets environment
  • Experience building production-quality software with solid software engineering principles, testing and maintainable code
  • Familiarity with NumPy, Pandas and SciPy
  • Understanding of equities markets, financial instruments and data
  • Credit experience is advantageous but not essential
  • Collaboration with researchers and traders
  • Ownership and accountability for applications
  • Problem-solving and attention to data quality and reliability
  • Python
  • NumPy
  • Pandas

Skills

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See also