Job Title: Python Software Engineer – Financial Engineering
Position Overview
We are an Portfolio Risk Analytics Company seeking a highly skilled Python Software Engineer with a strong background in financial engineering to design, develop, and maintain quantitative financial applications. The ideal candidate has experience building analytical tools, pricing models, trading systems, or risk management platforms using Python and modern software engineering practices.
Responsibilities
Design, develop, and maintain Python applications for financial analysis and quantitative modeling.
Build and optimize pricing, valuation, and risk management models for financial instruments.
Develop data pipelines for processing market, economic, and alternative data.
Implement and maintain backtesting frameworks for trading and investment strategies.
Collaborate with quantitative researchers, traders, portfolio managers, and software engineers.
Optimize code for performance, scalability, and reliability.
Integrate applications with market data providers, databases, and APIs.
Write clean, maintainable, and well-documented code.
Develop automated testing and deployment pipelines.
Monitor production systems and troubleshoot technical issues.
Required Qualifications
Bachelor's, Master's, PhD's degree in Computer Science, Financial Engineering, Mathematics, Physics, Engineering, or a related quantitative field.
3+ years of professional Python development experience.
Strong knowledge of object-oriented programming and software design principles.
Experience with financial engineering concepts, including:
Derivative pricing
Fixed income analytics
Portfolio optimization
Risk management
Time series analysis
Experience with Python libraries such as:
NumPy
Pandas
SciPy
Statsmodels
scikit-learn
Experience working with SQL databases.
Familiarity with REST APIs and cloud platforms.
Experience using Git and CI/CD workflows.
Strong analytical and problem-solving skills.
Preferred Qualifications
Experience developing algorithmic trading systems.
Knowledge of stochastic calculus, Monte Carlo simulation, and numerical optimization.
Familiarity with financial data providers (S&P, Bloomberg, Refinitiv, ICE, Polygon.io, etc.).
Experience with distributed computing or high-performance computing.
Knowledge of Docker, Kubernetes, or cloud infrastructure (AWS, Azure, or GCP).
Experience with machine learning applied to financial markets.
Familiarity with C++, Rust, or Java is a plus.
Technical Skills
Python
NumPy
Pandas
SciPy
SQL
Git
Linux
Docker
REST APIs
Financial Modeling
Quantitative Finance
Risk Analytics
Time Series Analysis
Desired Personal Attributes
Strong quantitative reasoning
Excellent communication skills
Attention to detail
Ability to work independently and collaboratively
Passion for financial markets and technology
Commitment to writing high-quality, maintainable software
Nice-to-Have Experience
Quantitative research
Options pricing
Fixed income analytics
Portfolio construction
Market risk or credit risk systems
Backtesting platforms
Financial data engineering
AI/ML applications in finance