We are looking for a Junior Quantitative Risk Analyst for an International Asset Management company based in Madrid.Functions:Risk Assessment: Conduct in-depth analysis of risk exposures and potential vulnerabilities. Evaluate the impact of market events, financial products, and regulatory changes on the company's risk profile. Monitor risk metrics, such as Value-at-Risk (VaR), stress testing, scenario analysis, and sensitivity analysis.Risk Modeling: Develop, implement, and enhance quantitative risk models to assess market, credit, and liquidity risks. Utilize statistical and mathematical techniques to analyze large datasets, identify patterns, and forecast potential risks.Risk Reporting: Support the preparation of risk reports and presentations for senior management and portfolio management. Communicate complex risk concepts and findings in a clear and concise manner. Ensure accurate and timely reporting of risk metrics, key risk indicators, and risk appetite frameworks.Risk Mitigation Strategies: Collaborate with cross-functional teams, including traders, portfolio managers, and other risk officers, to assess risk mitigation strategies and action plans. Contribute to the development of risk management policies, procedures, and controls.Data Analysis and Modeling: Utilize advanced statistical and econometric techniques to analyze historical data, identify correlations, and build robust risk models. Employ programming languages (Python/R) and quantitative tools to manipulate data, conduct simulations, and back-test risk models.Requirements:Bachelor or Master's Degree in mathematics, physics, engineering, finance, economics, econometrics, or a related field. A risk management relevant qualification like a FRM is desirable.Minimum 2 years of experience in the financial industry performing econometric/statistical modeling of multi-asset portfolios and/or quantitative empirical work.Experience with R or Python.Excellent analytical and quantitative skills, with strong attention to detail and ability to drive results.Self-starter who is accountable and motivated by collaborating with Risk Officers and PMs.Analytical and structured thinking with strong affinity for quantitative methods as well as a high level of initiative and a structured and goal-oriented approach.Previous exposure to non-traditional modeling techniques (e.G., "machine learning") and to modeling private assets.#J-18808-Ljbffr