Python/Quantitative Analysis Developer Company Overview CleverCX is a Charlotte-based fintech company founded in 2022. We focus on transforming how financial services companies engage with their clients digitally. CleverCX offers tools and platforms designed to modernize client interactions, emphasizing lead generation, financial planning, proposal creation, and AI-driven engagement. Job Overview: We are looking for a highly skilled Python Developer with a strong background in quantitative analysis and financial calculations to join our team as a part-time consultant. In this role, you will develop and optimize software systems for complex financial modeling, risk analysis, and other quantitative applications. Your work will directly contribute to building tools that support data-driven decision-making and innovative financial solutions. Key Responsibilities: Financial Modeling & Calculations: Design, implement, and optimize algorithms and models for financial analysis, including risk models, portfolio management, pricing strategies, and other quantitative financial applications. Data Processing & Analysis: 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. Algorithm Development: Develop mathematical models, simulations, and optimization algorithms for financial forecasting, market analysis, and trading strategies. Optimization: Identify areas for performance improvement in financial models and data processing pipelines. Optimize code for speed and scalability. Tool Development: Build tools and libraries to support quantitative analysis, including backtesting platforms, data visualization tools, and financial calculators. Collaboration: 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. Testing & Documentation: Ensure the reliability of financial calculations and models through robust unit testing. Document algorithms, code, and systems for future use and clarity. Required Qualifications: Strong Python Programming Skills: Proficiency in Python, with experience in libraries such as NumPy, Pandas, SciPy, Matplotlib, and SymPy for numerical and financial analysis. Quantitative Analysis Background: 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. Mathematical & Statistical Expertise: In-depth knowledge of mathematics, particularly probability theory, stochastic processes, optimization, and time series analysis. Experience with Financial Calculations: 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. Data Handling & Manipulation: Expertise in handling large datasets, performing statistical analysis, and using SQL or NoSQL databases to retrieve and process financial data. Performance Optimization: Ability to write high-performance code, optimize algorithms, and work with large-scale data processing frameworks. Version Control: Proficiency in Git for version control and collaboration within development teams. Problem Solving & Debugging: Strong analytical and troubleshooting skills, with a methodical approach to solving complex quantitative and technical problems. Preferred Qualifications: Advanced Degree: Master’s in Quantitative Finance, Mathematics, Physics, Statistics, or related field and/or Professional Designations: Chartered Financial Analyst (CFA) or Chartered Alternative Investment Analyst (CAIA). Financial Software Experience: Experience working with financial modeling platforms, trading platforms, or financial risk management tools. Cloud Computing: Familiarity with cloud services such as AWS, GCP, or Azure for deploying financial applications or performing large-scale data processing. Big Data Technologies: Experience with Hadoop, Spark, or other big data frameworks for processing large financial datasets. Machine Learning: Experience with machine learning techniques applied to quantitative finance, such as predictive modeling or algorithmic trading strategies. Job Types: Part-time, Contract Pay: $50.00 - $70.00 per hour Expected hours: 5 – 20 per week Schedule: Choose your own hours Experience: REST: 5 years (Preferred) Java: 1 year (Preferred) Experience: REST: 5 years (Preferred) Java: 1 year (Preferred) Work Location: Remote