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Risk Quantitative Analyst Jobs (Hybrid work)

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Quantitative Analyst AVP- Credit Risk
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Join Barclays in New York as a Quantitative Analyst AVP for Credit Risk. You will design and implement statistical and machine learning models using Python, R, and SQL to solve complex business problems. This role involves close collaboration with technology teams to operationalize solutions, ens...
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United States , New York
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100000.00 - 160000.00 USD / Year
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Barclays
Expiration Date
Until further notice
Senior Quantitative Risk Analyst
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Join Allianz plc as a Senior Quantitative Risk Analyst in Dublin. You will steer financial recovery plans, calibrate internal models, and conduct stress testing. This role requires 5+ years in risk management and offers a hybrid model with strong growth opportunities.
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Ireland , Dublin
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Not provided
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Allianz
Expiration Date
Until further notice
Quantitative Risk Analyst
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Join Octopus Energy in London as a Quantitative Risk Analyst. Develop sophisticated models using Python and SQL for power, gas, and renewable PPA risk. You will implement VaR, Monte Carlo simulations, and manage portfolio optimisation. Play a key role in shaping our global market risk function wi...
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United Kingdom , London
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Not provided
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Octopus Energy
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Until further notice
Explore a world of challenging and rewarding Risk Quantitative Analyst jobs, a critical profession at the intersection of high finance, advanced mathematics, and cutting-edge technology. Risk Quantitative Analysts, often called "Quants," are the architects of the mathematical models that financial institutions rely on to measure, manage, and mitigate financial risk. Their work forms the backbone of prudent risk management, ensuring stability and regulatory compliance in a complex global marketplace. Professionals in these roles are primarily responsible for researching, designing, developing, and maintaining sophisticated statistical models. These models quantify various types of risk, including credit risk (the risk of borrower default), market risk (losses from market movements), and counterparty credit risk (exposure from derivatives and trading partners). A core function involves applying these models for critical purposes such as calculating regulatory capital under frameworks like Basel III, conducting economic stress testing to simulate adverse scenarios, and forecasting potential financial losses. Beyond pure development, their day-to-day responsibilities encompass rigorous model validation, back-testing against historical data, and comprehensive documentation to meet stringent internal and regulatory audit standards. They also act as key advisors, translating complex model outputs into actionable insights for risk managers, traders, and senior executives. The typical path to securing Risk Quantitative Analyst jobs requires a strong academic foundation, usually a Master's or Ph.D. in a highly quantitative field such as Mathematics, Statistics, Physics, Financial Engineering, Econometrics, or Computer Science. Candidates must possess deep theoretical knowledge in stochastic calculus, probability theory, linear algebra, and time-series analysis. Practical programming proficiency is non-negotiable, with Python, R, C++, and SQL being industry standards for model implementation and data analysis. A solid understanding of financial products—from vanilla bonds to complex derivatives across asset classes—and the economic principles that drive them is essential. Furthermore, successful analysts blend this technical expertise with exceptional analytical problem-solving skills and the ability to communicate intricate quantitative concepts clearly to non-technical stakeholders. The profession demands intellectual curiosity, a meticulous attention to detail, and a commitment to staying abreast of evolving financial regulations, products, and computational techniques. For those with a passion for solving high-stakes problems with mathematical rigor, Risk Quantitative Analyst jobs offer a dynamic career at the very heart of modern finance. These positions are pivotal in safeguarding financial institutions, making them both intellectually stimulating and fundamentally important to the global financial system.

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