Orchestrade
Financial Engineer
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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.
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Required Qualifications:
Education: Master’s degree in Financial Engineering, Computer Science, Mathematics, Physics, or a related field.
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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.
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