Python Quantitative Developer – Cross Asset XVA & Capital Analytics

Opportunity

We are looking for an experienced C++/Python Quantitative Developer to join a high-impact quantitative analytics team focused on Cross Asset XVA and Capital Analytics.

This is a senior technical role combining quantitative modelling, software engineering and financial markets, with responsibility for developing analytics libraries used across pricing and risk management. You will work closely with Traders, Structurers, Quantitative Analysts and technology teams to deliver robust, scalable and production-ready solutions.

Key Responsibilities

• Develop and maintain quantitative analytics libraries supporting pricing and risk management.
• Implement and support quantitative models using a combination of mathematical and computer science techniques.
• Develop pricing and valuation models using numerical methods, including Monte Carlo simulations and PDE solvers.
• Build high-quality software using C++ and Python, alongside technologies such as C#/.NET, Java, SQL and kdb.
• Apply object-oriented design principles and strong software engineering practices to quantitative applications.
• Work with market data and develop analytical solutions for complex financial instruments.
• Collaborate closely with Traders, Structurers, Quantitative Analysts and Technology teams.
• Partner with control functions including Market Risk, Credit Risk, Finance, Legal, Compliance and Audit.
• Contribute to appropriate governance, controls and risk-management processes.
• Provide technical expertise and contribute to the wider direction of the quantitative technology function.

Requirements

Essential Experience

• Strong professional experience in a quantitative development, quantitative modelling or analytics role, ideally within financial services.
• Strong Python programming experience.
• Experience with C#/.NET and SQL.
• Strong understanding of software design principles and object-oriented programming.
• Experience working with market data.
• Strong knowledge of statistics and probability.
• Ability to apply probability theory and numerical techniques to complex financial instruments.
• Experience with quantitative methods and mathematical finance.
• Understanding of investments and financial products.
• Strong communication skills with the ability to work effectively with both technical and business stakeholders.

Nice to have

Desirable Technical Experience

• Monte Carlo modelling
• Partial Differential Equation (PDE) solvers
• Numerical analysis
• Quantitative pricing and risk analytics
• Hardware acceleration
• kdb / time-series market data
• Java
• SQL
• High-performance quantitative applications

Ideal Candidate

The ideal candidate will be a strong software engineer with genuine quantitative capability, rather than purely a software developer or purely theoretical quant. You should be comfortable moving between C++ development, Python analytics, mathematical modelling and financial markets, while being able to communicate effectively with Traders, Structurers and senior stakeholders.

A Bachelor's or Master's degree in a relevant discipline is expected, with a Master's or PhD preferred.

Core Technology Stack

C++ | Python | C#/.NET | Java | SQL | kdb | Mathematical Finance | Statistics & Probability | Monte Carlo | PDEs | Market Data | Quantitative Analytics | Pricing & Risk

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.