Quantitative Risk Management Expert

3 weeks ago


Bengaluru, Karnataka, India Société Générale Assurances Full time

As a member of our team, you will be responsible for performing the calibration of diffusion volatilities for underlying risk factors used in the context of counterparty risk. Your main missions will be to:

  • Perform the calibration of diffusion volatilities for underlying risk factors used in the context of counterparty risk
  • Perform the back test of the distribution of simulated risk factors
  • Suggest potential improvements in code/algorithms linked to model implementation in system in order to better explain calibrated parameters fluctuations
  • Evaluate, in coordination with the other RISQ/RMA teams, the actions to be conducted to improve the back testing performance: granularity improvement of the risk factor modeling, inclusion of additional risk factors in the model, refinement of proxies, RISQ valuation refinement, etc.
  • Prepare presentation and present findings in relation to back-testing exercises to the model committees on risk factor themes
  • Carry out monitoring and permanent supervision checks to ensure the sustainability of the internal model: monitoring of proxies
  • Contribute to the transmission of the regulatory culture within the Bank
  • Provide quantitative support to the Paris Team on projects aimed at addressing recommendations

Profile required:

  • Masters or PhD (or similar) in a quantitative subject such as Mathematics, Physics, Economics, or Finance, or a track record of performance that demonstrates this ability
  • Background in a quantitative role within risk management across asset classes, equities/rates/fx/credit in a financial institution
  • Excellent knowledge and understanding of a wide variety of model development and validation statistical techniques covering primarily credit and market risk (Model diffusion, statistics, Monte Carlo...)
  • Significant experience in either model development or in model validation, hands-on experience in model development, model specification, model selection, model testing and validation
  • Knowledge of computing and scripting languages (Python, R...)


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