Python Quant Developer- Leading Systematic Fund - J12510

Our client, a top-tier systematic fund, is seeking a Quantitative Developer to join its centralized fund team. This role is pivotal in bridging the gap between sophisticated mathematical research and high-performance execution. You will be responsible for the end-to-end development of the trading lifecycle, from designing robust backtesting engines to optimizing production-grade execution algorithms.

Core Responsibilities

• Strategy Engineering: Architect, implement, and deploy complex quantitative strategies and execution logic primarily using Python.

• Infrastructure Development: Build and maintain high-fidelity backtesting environments and research frameworks capable of handling high-frequency market data.

• Research Partnership: Collaborate directly with PM and Quantitative Researchers to translate theoretical models into high-performance, production-grade code, ensuring zero-drift between simulation and live execution.

• Performance Optimization: Profile and tune system components for maximum throughput, low latency, and efficient memory management to maintain a competitive edge in fast-moving markets.

• Data Pipeline Engineering: Design and manage scalable pipelines for processing vast datasets (tick-by-tick and alternative data) to empower both research and real-time trading operations.

Requirements & Qualifications

Professional Experience

• Tenure: 3–5 years of hands-on experience in a Python Quantitative Development role.

• Industry Background: Proven track record within a top-tier global hedge fund, proprietary trading firm, or quantitative investment manager.

• Delivery: Demonstrated success in shipping mission-critical trading software and supporting live production environments.

Technical Skill Set

• Python Expertise: Mastery of the Python ecosystem (NumPy, Pandas) for high-performance data analysis and research tooling.

• System Programming: Deep understanding of multi-threaded programming, network protocols (TCP/UDP), and Linux kernel/system internals.

• Data Architecture: Familiarity with high-performance time-series databases (e.g., kdb+/q) and modern SQL/NoSQL storage solutions.

Quantitative & Market Acumen

• Market Sense: A solid understanding of the quantitative strategy lifecycle, including signal generation, portfolio construction, and market impact.

• Strategy Exposure (Preferred): Prior experience with Statistical Arbitrage or Event-Driven strategies is highly desirable, including an understanding of the specific data and execution nuances required for these styles.

Educational Background

• Academic Excellence: Bachelor’s, Master’s, or PhD from a leading university in Computer Science, Mathematics, Physics, Engineering, or a related quantitative discipline.

If this outstanding opportunity sounds like your next career move, please submit through "Apply Now" or send your resume in Word format to Lu Zhang at resume@pinpointasia.com and put Python Quant Developer- Leading Systematic Fund - J12510 in the subject header.

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