Perform bespoke tactical risk analysis in response to requests from senior management for data-driven insight, coordinating with other Enterprise Risk Management teams such as Stress Testing, IFRS9 and Portfolio Risk in doing so.
Research, design, implement and validate cutting-edge analytics and data visualization techniques to achieve targeted outcomes, such as bringing predicted loss estimates closer to experience while ensuring consistency with the model ecosystem.
Interact with internal stakeholders across the bank to explain the modelling methodologies used to enable them to better understand the output from the models.
Contributing/leading development of sandbox/prototype solutions coordinating with other areas of ERA as appropriate.
Identify opportunities for solutions to be leveraged across businesses or functions to broaden their scope of use, improving the consistency and efficiency or risk analysis.
Provide input into priorities across ERA by identifying opportunities to adjust data, IT, or model strategies.
Work with data and systems teams in setting up data flows into bank systems to enable live calculation of the predictive models
Structured conceptual thinker with strong inter-personal and communication skills to work effectively with stakeholders from different functions and different cultural backgrounds.
Understanding of banking, IFRS9 and credit risk model concepts would be advantageous.
Strong degree in any discipline with substantial quantitative component (e.g. Physics, Mathematics, Statistics, Actuarial Sciences, Biostatistics, etc.).
Four years' experience in a predictive analytics or AI/ML role.
Expertise in analytical programming, especially Python, R, SAS, or other forms of machine learning or mathematical modelling, with experience in data handling.
Motivated self-starter comfortable with uncertainty and passionate about problem solving.
Internal Number: 5503826
About Standard Chartered Bank
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