Python Developer - Quantitative

We are seeking a Senior Python Developer with 3-4 years of experience and a strong understanding of stock market dynamics, technical indicators, and trading systems. You'll take ownership of backtesting frameworks, strategy optimization, and developing high-performance, production-ready trading modules. The ideal candidate is someone who can think critically about trading logic, handle edge cases with precision, and write clean, scalable, and testable code. You should be comfortable working in a fast-paced, data-intensive environment where accuracy and speed are key.

Responsibilities

• Design and maintain robust backtesting and live trading frameworks.
• Build modules for strategy development, simulation, and optimization.
• Integrate with real-time and historical market data sources (e. g., APIs, databases).
• Use libraries like Pandas, NumPy, TA-Lib, Matplotlib, SciPy, etc., for data processing and signal generation.
• Apply statistical methods to validate strategies (mean, regression, correlation, standard deviation, etc. ).
• Optimize code for low-latency execution and memory efficiency.
• Collaborate with traders and quants to implement and iterate on ideas.
• Use Git and manage codebases with best practices (unit testing, modular design, etc. ).
  
  

Requirements

• 3-4 years of Python development experience, especially in data-intensive environments.
• Strong understanding of algorithms, data structures, and performance optimization.
• Hands-on with technical indicators, trading strategy design, and data visualization.
• Proficient with Pandas, NumPy, Matplotlib, SciPy, TA-Lib, etc.
• Strong SQL skills and experience working with structured and time-series data.
• Exposure to REST APIs, data ingestion pipelines, and message queues (e. g., Kafka, RabbitMQ) is a plus.
• Experience in version control systems (Git) and collaborative development workflows.
  
  

Preferred Experience

• Hands-on experience with trading platforms or algorithmic trading systems.
• Familiarity with order management systems (OMS), execution logic, or market microstructure.
• Prior work with cloud infrastructure (AWS, GCP) or Docker/Kubernetes.
• Knowledge of machine learning or reinforcement learning in financial contexts is a bonus.
  
  

This job was posted by Human Resource from Codeline Tech.