Quantitative Python Developer - Systematic Trading - J13085

Our client is a premier global quantitative investment manager building technology- driven research platforms. In this role, you will design and scale high-performance research infrastructure, backtesting engines, and distributed data pipelines. Prior financial experience is not required.

Key Responsibilities

• Build and scale core backtesting engines, simulation tools, and portfolio construction frameworks.
• Design clean, high-performance Python APIs and libraries to integrate research workflows into production.
• Develop scalable processing pipelines and distributed computing solutions for massive financial datasets.
• Maintain software engineering best practices, including CI/CD, automated testing, and performance profiling.
• Partner directly with Quantitative Researchers and Data Engineers to translate research needs into production software.

Requirements & Qualifications

• Degree (BS, MS, or PhD) in Computer Science, Mathematics, or a related STEM discipline.
• Advanced proficiency in Python and its scientific stack (NumPy, Pandas, Polars) with a focus on performance optimization.
• Strong command of software design, data structures, algorithms, and Linux environments.
• Proficiency with Git, CI/CD pipelines, automated testing, and profiling tools.

Open to tech, startup, or data engineering backgrounds—no prior finance experience required.

Preferred Qualifications

• Experience with distributed computing frameworks (Ray, Spark, Dask) or cloud platforms (AWS/GCP).
• Exposure to high-performance languages like C++ or Rust.
• Open-source contributions to scientific or numerical Python libraries.