Python Quantitative Analysis Developer

Summary

Join our team as a part-time consultant and leverage your expertise in Python development and quantitative finance. You will design, implement, and optimize software systems for complex financial modeling, risk analysis, and other quantitative applications. Your contributions will directly impact data-driven decision-making and innovative financial solutions. This role requires a strong background in quantitative analysis and financial calculations, proficiency in Python and relevant libraries, and experience with financial modeling and data processing. The position offers the flexibility of working from home.

Requirements

• Proficiency in Python, with experience in libraries such as NumPy, Pandas, SciPy, Matplotlib, and SymPy for numerical and financial analysis
• Solid understanding of quantitative finance, including financial modeling, asset pricing, risk management, and derivatives. Experience working with complex financial instruments such as options, bonds, and equities
• In-depth knowledge of mathematics, particularly probability theory, stochastic processes, optimization, and time series analysis
• Hands-on experience in implementing financial calculations such as Black-Scholes, Monte Carlo simulations, option pricing, risk metrics (VaR, CVaR), and other advanced quantitative techniques
• Expertise in handling large datasets, performing statistical analysis, and using SQL or NoSQL databases to retrieve and process financial data
• Ability to write high-performance code, optimize algorithms, and work with large-scale data processing frameworks
• Proficiency in Git for version control and collaboration within development teams
• Strong analytical and troubleshooting skills, with a methodical approach to solving complex quantitative and technical problems

Responsibilities

• Design, implement, and optimize algorithms and models for financial analysis, including risk models, portfolio management, pricing strategies, and other quantitative financial applications
• Write efficient Python code to handle large datasets, process financial data, and perform statistical analysis. Ensure accuracy and integrity of data used in financial calculations
• Develop mathematical models, simulations, and optimization algorithms for financial forecasting, market analysis, and trading strategies
• Identify areas for performance improvement in financial models and data processing pipelines. Optimize code for speed and scalability
• Build tools and libraries to support quantitative analysis, including backtesting platforms, data visualization tools, and financial calculators
• Work closely with quantitative analysts, data scientists, and other developers to understand requirements and deliver effective solutions. Collaborate with financial teams to understand domain-specific needs and translate them into code
• Ensure the reliability of financial calculations and models through robust unit testing. Document algorithms, code, and systems for future use and clarity

Preferred Qualifications

• Experience working with financial modeling platforms, trading platforms, or financial risk management tools
• Familiarity with cloud services such as AWS, GCP, or Azure for deploying financial applications or performing large-scale data processing
• Experience with Hadoop, Spark, or other big data frameworks for processing large financial datasets
• Experience with machine learning techniques applied to quantitative finance, such as predictive modeling or algorithmic trading strategies

Benefits

Work from home