Senior Quantitative Analyst (Risk Management)

Our client is a prestigious financial institution seeking a highly analytical and results-oriented Senior Quantitative Analyst to join their remote-first Risk Management team. This role is crucial for developing and implementing sophisticated risk models and strategies that protect the firm's assets and ensure regulatory compliance. As a fully remote position, you will collaborate with a distributed team of experts, leveraging cutting-edge technology to address complex financial challenges.

Responsibilities: Develop, validate, and implement quantitative models for market risk, credit risk, operational risk, and other financial risk areas. Perform complex statistical analysis and data mining on large datasets to identify potential risks and opportunities. Design and implement stress testing and scenario analysis frameworks. Contribute to the development and enhancement of the firm's risk appetite framework and policies. Collaborate with business lines to understand their risk profiles and provide quantitative support for strategic decision-making. Ensure models comply with regulatory requirements (e.g., Basel III, Dodd-Frank) and internal policies. Develop and maintain documentation for all quantitative models and methodologies. Stay current with advancements in quantitative finance, econometrics, machine learning, and regulatory changes. Communicate complex quantitative findings clearly and effectively to both technical and non-technical audiences. Mentor junior analysts and contribute to the overall knowledge sharing within the risk management function. Utilize programming languages such as Python, R, or C++ for model development and implementation. Contribute to the continuous improvement of data quality, model governance, and risk reporting processes. Qualifications: Master's or Ph.D. in a quantitative field such as Financial Engineering, Mathematics, Statistics, Economics, or Physics. Minimum of 6 years of experience in quantitative analysis, risk management, or a related role within the financial services industry. Strong theoretical and practical knowledge of statistical modeling, time series analysis, stochastic calculus, and financial mathematics. Proficiency in programming languages like Python (with libraries like NumPy, SciPy, Pandas), R, or C++. Experience with SQL and database management. Deep understanding of financial markets, instruments, and risk management principles. Familiarity with regulatory frameworks impacting financial institutions. Excellent analytical, problem-solving, and critical thinking skills. Ability to work independently and manage multiple priorities in a remote setting. Strong written and verbal communication skills, with the ability to present complex information clearly. Experience with machine learning techniques applied to finance is a plus. This is an outstanding opportunity to make a significant impact within a leading financial organization, working remotely on challenging and impactful projects.