Quantitative Python Developer - Systematic Trading - J13085

Pinpoint Asia; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Pinpoint Asia's client, a premier global quantitative investment manager, seeks an engineer to design and scale high‑performance research infrastructure, backtesting engines, and distributed data pipelines. No prior finance experience required, offering a rare entry into production research tooling.

You will collaborate with Quantitative Researchers and Data Engineers, build Python APIs and libraries, optimize performance with NumPy/Pandas/Polars, and ensure robust CI/CD, testing, and profiling

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.

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.

Skills

Python

NumPy

Pandas

Polars

Git

CI/CD

Automated testing

Profiling

Linux

Data structures

Algorithms

Performance optimization

Education

BS/MS/PhD in Computer Science, Mathematics or related STEM

Tools

Ray

Spark

Dask

AWS

GCP

Job description

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.