Job
Description
Python/Quant Engineer Key Responsibilities: Design, develop, and maintain scalable Python-based quantitative tools and libraries. Collaborate with quants and researchers to implement and optimize pricing, risk, and trading models. Process and analyze large datasets (market, fundamental, alternative data) to support research and live trading. Build and enhance backtesting frameworks and data pipelines. Integrate models with execution systems and trading platforms. Optimize code for performance and reliability in low-latency environments. Participate in code reviews, testing, and documentation efforts. Required Qualifications: 3-8 years of professional experience in quantitative development or similar roles. Proficiency in Python , including libraries like NumPy, Pandas, SciPy, Scikit-learn , and experience in object-oriented programming. Strong understanding of data structures, algorithms , and software engineering best practices. Experience working with large datasets, data ingestion, and real-time processing. Exposure to financial instruments (equities, futures, options, FX, fixed income, etc.) and financial mathematics. Familiarity with backtesting, simulation , and strategy evaluation tools. Experience with Git , Docker , CI/CD , and modern development workflows. Preferred Qualifications: Preferred Experience with C++ for performance-critical modules. Knowledge of machine learning techniques and tools (e.g., TensorFlow, XGBoost). Familiarity with SQL / NoSQL databases and cloud platforms (AWS, GCP). Prior experience in hedge funds, proprietary trading firms, investment banks, or financial data providers.
