2 дня назад
Software Developer (C++)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Developer (C++/ETF): Designing and developing equities and futures trading systems with an accent on performance optimization, latency reduction, and stable, scalable execution. Focus on building and improving order sending strategies, collaborating with traders and quantitative researchers, and exploring technologies for high-performance trading environments.
Location: Onsite in Bala Cynwyd, Pennsylvania (Philadelphia Area)
Company
is a quantitative trading firm that develops technology and strategies for listed financial products and derivatives markets.
What you will do
- Design and develop equities and futures trading systems.
- Work with traders and quantitative researchers to build, maintain, and improve order sending strategies.
- Enhance existing trading capabilities through stable, scalable, and optimized systems.
- Gather requirements, propose ideas, and deliver functionality through short development cycles.
- Investigate new technologies and apply strong object-oriented programming practices.
- Optimize systems that process massive amounts of data while minimizing operational risk.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related discipline, or a foreign equivalent.
- 5+ years of progressive experience developing software applications with C++.
- Thorough understanding of performance optimization and latency reduction methodologies.
- Strong attention to detail and accuracy.
- Ability to collaborate with software developers, traders, quants, and infrastructure teams.
Nice to have
- Familiarity with financial markets.
Culture & Benefits
- Work in an intellectually driven and highly collaborative environment with researchers, engineers, and traders.
- Contribute to firm-wide software solutions and systematic trading strategies.
- Access competitive employee perks and benefits.
- Work with machine learning, quantitative research, and large datasets applied to global markets.
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