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# Python Software Engineer - Financial EngineeringPosition

- **Company:** PORTFOLIO ANALYTICS, LLC
- **Location:** Guilford, CT, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Algorithmic Trading, Amazon Web Services, Business Analytics Applications, Automation of Tests, Microsoft Azure, C++ (Programming Language), Cloud Computing, Program Optimization, Databases, Continuous Integration, Linux, Distributed Systems, Python (Programming Language), Machine Learning, Monte Carlo Methods, NumPy, Object-Oriented Software Development, Backtesting, Standard Sql, Risk Management Information Systems, SciPy, Software Engineering, High Performance Computing, Delivery Pipeline, Git, Fastapi, Pandas, Scikit Learn, Solid Principles, Kubernetes, Information Technology, Statistics Packages, Restful APIs, Data Pipelines, Docker
- **Published:** September 26, 2026
- **Apply:** https://www.juju.com/job/16_712815c01

## About the Role

* 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

## Description

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., * 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.


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