Role Overview

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, back testing engines, and distributed data pipelines. Prior financial experience is not required.

Key Responsibilities

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

Requirements & Qualifications

1. Degree (BS, MS, or PhD) in Computer Science, Mathematics, or a related STEM discipline.
2. Advanced proficiency in Python and its scientific stack (NumPy, Pandas, Polars) with a focus on performance optimization.
3. Strong command of software design, data structures, algorithms, and Linux environments.
4. Proficiency with Git, CI/CD pipelines, automated testing, and profiling tools.
5. Open to tech, startup, or data engineering backgrounds—no prior finance experience required.

Preferred Qualifications

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

If this outstanding opportunity sounds like your next career move, please submit through "Apply Now" or send your resume in Word format to Matt Chung atresume@pinpointasia.com and putQuantitative Python Developer - Systematic Trading - J13085 in the subject header.

Data provided is for recruitment purposes only.

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