Senior Python Software Engineer – Quantitative Trading & Research
Build high-performance Python systems powering quantitative research, systematic trading, automation, analytics, and risk workflows, collaborating with traders, researchers, and engineers across a sophisticated technology environment.
What You’ll Do:
- Develop, test, deploy, and maintain high-performance Python applications.
- Build scalable tools supporting systematic trading and quantitative research.
- Develop automation, analytics, visualization, and workflow optimization solutions.
- Enable researchers to run large-scale computations and backtesting.
- Work closely with traders, quants, researchers, and engineering teams.
- Own projects throughout the full software development lifecycle.
- Optimize systems while balancing latency, throughput, scalability, and maintainability.
- Apply modern automated testing, CI/CD, and daily deployment practices.'
Your Responsibilities Will Include:
- Engineering Python-based platforms that take trading strategies from prototype to production.
- Creating business-critical applications for risk management and operational workflows.
- Developing research tooling for distributed computing and large-scale quantitative analysis.
- Implementing reliable automation solutions that improve productivity and efficiency.
- Gathering requirements and translating complex stakeholder needs into practical software.
- Maintaining robust, scalable systems across Linux, Docker, and Kubernetes environments.
- Working with technologies such asPandas, NumPy, SciPy, Celery, Dask, and Spark.
- Continuously improving software performance, reliability, testing, and deployment processes.
Why Join Us:
- Work at the intersection ofsoftware engineering, quantitative research, and systematic trading.
- Solve technically challenging problems involving high-performance and distributed systems.
- Collaborate directly with experienced traders, quants, researchers, and engineers.
- Build technology that directly influences sophisticated trading and research workflows.
- Gain exposure to modern cloud, containerization, automation, and data-processing technologies.
- Enjoy an environment where engineers have genuine ownership from concept through production.
About You:
- 5+ years of professional software engineering experience with strong Python expertise.
- Strong knowledge of numerical computing and data-processing technologies.
- Experience with automated testing and CI/CD pipelines.
- Familiarity with Docker, Kubernetes, and Linux.
- Exposure to distributed computing and cloud-based data processing.
- Excellent problem-solving skills with a proactive approach to technical challenges.
- Strong communication and cross-functional collaboration abilities.
- Curious, adaptable, and eager to learn quantitative finance and financial markets.
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