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Quantitative Risk Modeling Specialist

2 months ago

London, Greater London, United Kingdom Cititec Talent Full time
About the Role

Cititec Talent is seeking a highly skilled Senior Quantitative Risk Analyst/Developer to join our Quant Modeling team. As a key member of our team, you will be responsible for developing and enhancing our risk management systems, focusing on Value-at-Risk (VaR) models and advanced risk tools to support various trading activities.

Key Responsibilities
  • Design and Develop New VaR Models: Create and implement new VaR models using historical and factor-based approaches, researching other VaR models with emphasis on commodity market volatility and seasonality.
  • Build and Enhance Quantitative Models: Develop, test, and maintain quantitative models specialized for the needs of trading and risk managers, including derivatives pricing and volatility marking, with a primary focus on commodities derivatives and exposure to other products such as equity and rates derivatives.
  • Contribute to Risk Management Capabilities: 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.
  • Counterparty Risk Expertise: Emphasize counterparty risk with projects on PFE/XVA and initial margin calculations.
  • Improve Risk Reporting Tools: Improve and extend existing risk reporting tools, including risk analysis and P&L attribution.
Requirements
  • Advanced Degree: Hold an advanced degree in a quantitative field such as Mathematics, Statistics, Financial Engineering, or a related discipline.
  • Quantitative Experience: Possess 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, with good knowledge of the commodities derivatives trading landscape.
  • Proven Track Record: Demonstrate a proven track record in market risk, developing and implementing VaR models, with deep knowledge of the modelling approaches and their strengths/weaknesses.
  • Expert Knowledge: Possess expert knowledge of risk and understanding of the application of complex mathematical concepts related to Monte Carlo, options pricing, and time series analysis.
  • Programming Skills: Have advanced programming skills, ideally in Python.
  • Problem-Solving Skills: Possess strong problem-solving and troubleshooting skills.