Quantitative Risk Analyst - Derivatives
Our client, a leading financial institution, is seeking a highly analytical Quantitative Risk Analyst specializing in derivatives to join their team in Cincinnati, Ohio, US . This hybrid role offers a dynamic work environment combining in-office collaboration with remote flexibility. You will be responsible for developing, implementing, and maintaining sophisticated risk models for a diverse portfolio of derivative products, including equities, fixed income, foreign exchange, and commodities. Your core duties will involve stress testing portfolios, calculating Value-at-Risk (VaR) and Expected Shortfall (ES), assessing counterparty credit risk, and contributing to regulatory reporting.
The successful candidate will possess a strong academic background with a Master's or Ph.D. in a quantitative field such as Financial Engineering, Mathematics, Statistics, Physics, or Economics. Proven experience in quantitative finance, specifically with derivatives pricing and risk management, is essential. Proficiency in programming languages commonly used in finance, such as Python (with libraries like NumPy, SciPy, Pandas), R, or C++, is required. You should have a deep understanding of financial markets, market risk methodologies, and regulatory frameworks (e.g., Basel III, Dodd-Frank). Excellent communication skills are necessary to explain complex quantitative concepts to both technical and non-technical stakeholders, including senior management and regulators. The ability to work effectively in a fast-paced, team-oriented environment, manage multiple projects, and meet tight deadlines is critical. Familiarity with data visualization tools and SQL databases would be an advantage. This role is ideal for a motivated individual looking to apply advanced quantitative techniques to complex financial challenges within a reputable banking organization.
The successful candidate will possess a strong academic background with a Master's or Ph.D. in a quantitative field such as Financial Engineering, Mathematics, Statistics, Physics, or Economics. Proven experience in quantitative finance, specifically with derivatives pricing and risk management, is essential. Proficiency in programming languages commonly used in finance, such as Python (with libraries like NumPy, SciPy, Pandas), R, or C++, is required. You should have a deep understanding of financial markets, market risk methodologies, and regulatory frameworks (e.g., Basel III, Dodd-Frank). Excellent communication skills are necessary to explain complex quantitative concepts to both technical and non-technical stakeholders, including senior management and regulators. The ability to work effectively in a fast-paced, team-oriented environment, manage multiple projects, and meet tight deadlines is critical. Familiarity with data visualization tools and SQL databases would be an advantage. This role is ideal for a motivated individual looking to apply advanced quantitative techniques to complex financial challenges within a reputable banking organization.