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Our client is a top tier Investment Bank that have recently started building a Machine Learning Centre of Excellence to ensure that risks posed by ML models are captured accurately and consistently across various Lines of Business. Such models are currently used by the bank to detect fraud, improve marketing techniques, and optimize order routing in markets, among other things.
The group oversees model risk and conducts independent model reviews and provides guidance around a model's appropriate usage. This role will require you to run a team to quantitatively evaluate complex AI / ML models, and also build benchmark models in the process of evaluating these complex models.
Evaluate conceptual soundness of ML model techniques, specifications and feature sets; reasonableness of assumptions; reliability of inputs; completeness of testing performed; correctness of implementation; and suitability / comprehensiveness of performance metrics and risk measures.
Measure the potential impact of model limitations, convergence errors or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from benchmark models.
Evaluate the risk posed by non-transparency and non-linearity in ML models, and suggest ways to mitigate such risks.
Liaise with Developers, Finance, and Risk professionals to monitor usage and performance of the models.
Work with colleagues to evaluate econometric and mathematical models developed by the office of the Chief Investment Officer (CIO), and various other lines of business such as the retail bank, commercial bank and investment bank.
Cogently document findings.
Desirable Skills, Experience, And Qualifications
A Ph.D. in a quantitative field such as Finance, Economics, Math, Physics or Engineering is required.
7-10 years relevant experience.
Experience in development of AI / ML models and use of large data sets is required. You must be up to speed on the very latest ML techniques.
Understanding of statistics / econometrics.
Thorough knowledge of at least one programming language such as Matlab, R, Python, C/C++, etc.