100% Remote // Quantitative Finance Consultant- Data Science Python

100% Remote Quantitative Finance Professional with Data Science, Python Contract Position Overview We are seeking a highly analytical finance professional to develop and implement data-driven investment and risk management strategies. This role focuses on systematic, model-based approaches to portfolio construction, derivatives analysis, and financial risk control. The ideal candidate combines strong quantitative skills with practical experience in financial markets. Key Responsibilities 1. Systematic Strategy Development • Design and implement rules-based investment strategies. • Build algorithmic models for asset allocation, signal generation, and trade execution. • Continuously improve models using statistical and machine learning techniques. 1. Derivatives & Structured Products • Analyze and price options, futures, swaps, and other derivatives. • Develop hedging strategies to manage market exposure. • Monitor derivative positions and manage associated risks. 1. Risk Management & Analytics • Measure and monitor market, credit, and liquidity risks. • Calculate and interpret Value at Risk (VaR) and stress testing metrics. • Develop risk dashboards and reporting frameworks. 1. Factor-Based Portfolio Management • Research and implement factor models (e.g., value, momentum, volatility). • Construct and optimize multi-factor portfolios. • Evaluate factor performance across asset classes. 1. Back-Testing & Performance Analysis • Conduct rigorous historical back-testing of trading strategies. • Validate models and ensure robustness under different market conditions. • Analyze alpha generation and benchmark-relative performance. Required Qualifications • Bachelor’s or Master’s degree in Finance, Mathematics, Statistics, Engineering, Physics, or related quantitative field. • Strong programming skills (Python required; experience with SQL, R, or C++ is a plus). • Solid understanding of financial markets, derivatives, and portfolio theory. • Experience with data analysis, statistical modeling, and financial datasets. • Knowledge of risk metrics (VaR, CVaR, stress testing frameworks). Preferred Skills • Experience with machine learning in financial applications. • Familiarity with trading systems and market microstructure. • Knowledge of optimization techniques and factor modeling. • Strong problem-solving and critical thinking abilities. • Clear communication skills to explain complex quantitative concepts.