Financial Engineer

About Orchestrade Orchestrade is the market leading complete cross asset front-to-back trading and risk management platform used by investment banks, hedge funds, asset managers, private banks, energy and utility companies. A trusted technology partner that truly understands and meets the needs of firms, from start-up operations to the largest global enterprises. About the Position This position is ideal for anyone who is interested in working in a FinTech company as a career. The candidate will have great opportunities to work on financial derivatives products as well as energy/commodity derivative products. Job Summary: We are looking for a Financial Engineer to join our team and contribute to the testing, validation, and optimization of complex financial models, algorithms, and systems. This role is perfect for an individual who has a strong understanding of financial engineering principles, combined with a passion for quality assurance and testing in a highly dynamic environment. The Financial Engineer will play a key role in ensuring the robustness, accuracy, and performance of financial tools and applications before they are deployed in real-world trading and risk management scenarios. Key Responsibilities:

• Test Planning & Strategy: Develop and implement comprehensive test plans for financial models, algorithms, and applications. Ensure that testing strategies cover all functional, integration, and performance aspects of financial systems.
• Test Execution & Automation: Write and execute test cases to validate the accuracy and efficiency of financial models (e.g., derivatives pricing, portfolio optimization). Automate testing processes where possible to improve efficiency and scalability.
• Model Validation: Collaborate with quantitative analysts and developers to validate mathematical models used in pricing, risk management, and trading algorithms. Ensure that models produce expected outcomes and align with market conditions.
• Performance & Stress Testing: Design and execute performance and stress tests on financial systems, ensuring they can handle large datasets and complex calculations under various market conditions.
• Bug Identification & Resolution: Identify and report bugs, discrepancies, and performance issues. Work closely with development teams to troubleshoot and resolve issues quickly and effectively.
• Quality Assurance of Data: Test the integrity, accuracy, and reliability of data inputs used by financial models and systems. Ensure data quality in high-frequency trading environments and real-time risk monitoring systems.
• Documentation & Reporting: Document test procedures, results, and issues identified. Prepare clear, actionable reports and communicate findings to both technical and non-technical stakeholders.
• Collaboration: Work closely with financial engineers, developers, and risk managers to ensure models and systems are robust, accurate, and ready for deployment.
• Continuous Improvement: Stay updated with the latest advancements in financial testing techniques and tools. Propose and implement improvements to the testing process to increase efficiency and coverage. Required Qualifications:
• Education: Master's degree in Financial Engineering, Computer Science, Mathematics, Physics, or a related field.
• Experience: 1-3 years of experience in testing financial models, systems, or applications. Experience in a quantitative finance or algorithmic trading environment is a plus.
• Technical Skills:
• Strong knowledge of financial products, financial markets, and mathematical modeling.
• Proficiency in programming languages such as C# for automation and testing.
• Familiarity with financial data platforms like Bloomberg or similar.
• Knowledge of data structures, time series, and high-performance computing environments.
• Analytical Skills: Ability to analyze complex models and systems from a testing perspective. Solid understanding of risk management, pricing models, and quantitative analysis.
• Attention to Detail: Meticulous attention to detail when validating financial data, model outputs, and system behavior under different test scenarios.