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, backtesting engines, and distributed data pipelines. Prior financial experience is not required.
Â
Key Responsibilities
Build and scale core back testing 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.
Â
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.
Â
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.
Â
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 at resume@pinpointasia.com and put Quantitative Python Developer - Systematic Trading - J13085 in the subject header.
Â
Data provided is for recruitment purposes only.
