Python Risk PnL Developer

A Leading Financial Technology Firm is seeking a skilled Python Risk PnL Developer to design, build, and support enterprise applications used in Risk Management and P&L reporting. In this quantitative development role, you will implement and maintain Python applications supporting core risk metrics, including Value at Risk (VaR), asset valuation, derivative pricing, and P&L attribution. Furthermore, you will build and integrate high-performance RESTful APIs to facilitate seamless financial data exchange. Consequently, this position is crucial for delivering reliable risk intelligence to trading and risk desks.

The Python Risk PnL Developer must combine strong Object-Oriented Programming (OOP) mastery in Python with a solid understanding of financial risk analytics and P&L reporting workflows. Working alongside risk managers, quantitative analysts, and enterprise architecture squads, you will investigate complex system defects, optimize algorithmic performance, and enhance platform scalability. Therefore, the organization is looking for an analytical developer who writes clean, maintainable code with minimal supervision. If you want to engineer high-throughput risk reporting systems, this position is for you.

Key Responsibilities

• Design, build, deploy, and maintain robust Python applications supporting enterprise Risk Management and P&L reporting.
• Implement and support quantitative calculation engines for derivative pricing, portfolio valuation, VaR, and P&L attribution.
• Architect, configure, and integrate secure RESTful APIs to stream data across trading desks and risk systems.
• Investigate, debug, and resolve complex technical issues and calculation defects across production risk pipelines.
• Enhance application throughput, reduce runtime latency, and optimize system scalability for enterprise risk workloads.
• Collaborate actively with risk managers, financial engineers, and business analysts to translate financial models into code.
• Maintain clean, modular codebases following Object-Oriented Programming (OOP) standards and software engineering best practices.

Requirements and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Quantitative Finance, Software Engineering, or a related discipline.
• 5-8 Years of hands-on professional software development experience specializing in Python programming.
• Strong expertise in Object-Oriented Programming (OOP), modular design patterns, and RESTful API development.
• Solid functional understanding of financial risk concepts: Pricing, Asset Valuation, Value at Risk (VaR), and P&L Attribution.
• Proven debugging, analytical problem-solving, and cross-functional technical communication capabilities.