Python Software Engineer Financial Engineering

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