Manager- Decision Science

Contract Type
Academic title
Higher degree (any)
Job description


Treasury & Operational Risk Analytics team is a centrally managed team that is responsible for model development, model risk governance, monitoring performance, backtesting and define future action for all Regulatory Capital models (IMA and IMM).

Traded risk models include:

  • Market Risk models;
  • Counterparty Credit Risk models;
  • Margin models;
  • Add-on models;
  • Economic Capital. The team is a critical part of First Line of Defense (FLoD) from Model Risk perspective and is essential in meeting Regulatory and Audit requirement for the business.

What you’ll do:

The position is of Machine Learning and Artificial Intelligence SME for quantitative finance modelling and will functionally report into Global Counterparty Credit Risk (CCR) Model development lead.

The jobholder will be located in Traded, Treasury & Operational Risk Analytics,


Key responsibilities:

  • Use Deep Learning frameworks in use cases in derivatives modelling such as Pricing and Monte Carlo Simulation
  • Area of work includes SA-CVA, XVA, Simulation & Pricing models, Collateral & Margining models and multiple other CCR specific model development projects.
  • Perform activities pertaining to First Line of Defense based on the CCR Model Risk Management Framework
  • Model development based on best industry practice
  • Model calibration, monitoring and annual assessment
  • Support model users such as Traded Risk Managers, Front Office and Product Control etc.
  • Assist the Risk steward functions in second line of defense activities
  • Support all governance forums by providing timely inputs and escalating issues when required.

What you will need to succeed in the role:

  • Strong competence in Deep learning for Artificial Neural Network
  • Understanding of Neural Network to Time Series data (RNN, LSTM, HMM etc.)
  • Strong competence in Python coding & Big Data infrastructure (No SQL implementation)
  • Strong mathematical and statistical background
  • Any experience/case study of application of Neural Network in Derivatives modelling would be a big plus (whether it is in Pricing or in Monte Carlo processes in general).

Office Mode: Work from office

Shift: Indian

Other notes
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