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London, Greater London, United Kingdom Crédit Agricole SA Full time{"h1": "Quantitative Risk Analyst", "p": "We are seeking a highly skilled Quantitative Risk Analyst to join our team in London. As a key member of our model validation team, you will be responsible for ensuring the viability, robustness, and reliability of our pricing models. Your expertise in mathematical finance and programming skills will be essential in...
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London, Greater London, United Kingdom Crédit Agricole SA Full time{"h1": "Quantitative Risk Analyst", "p": "We are seeking a highly skilled Quantitative Risk Analyst to join our team in London. As a key member of our model validation team, you will be responsible for ensuring the viability, robustness, and reliability of our pricing models. Your expertise in mathematical finance and programming skills will be essential in...
Quantitative Risk Analyst
2 months ago
Cititec Talent is seeking a highly skilled Senior Quantitative Risk Analyst/Developer to join our Quant Modeling team. This role is critical in developing and enhancing the firm's risk management systems, focusing on Value-at-Risk (VaR) models and advanced risk tools to support various trading activities.
Key Responsibilities:- Build, enhance, test, and maintain quantitative models specialized for the needs of trading and risk managers, including derivatives pricing and volatility marking.
- Contribute to the firm's effort to calculate and aggregate raw risk metrics (greeks) from different trading systems to enhance the firm's overall risk management capabilities.
- Improve and extend existing risk reporting tools, including risk analysis and P&L attribution.
- Advanced degree in a quantitative field such as Mathematics, Statistics, Financial Engineering, or a related discipline.
- At least 5+ years of experience as a commodities quant or strategist or quantitative risk officer, gained in a Hedge Fund, Oil Major, Commodities Trading House, or a Bank.
- Proven track record in market risk, developing and implementing VaR models, with deep knowledge of the modelling approaches and their strengths/weaknesses.
- Experience in counterparty risk and PFE/XVA frameworks using commodities factor-based approaches and correlation analytics.
- Advanced programming skills, ideally in Python.