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Director - Model Risk - ML/AI

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Selby Jennings QRF 250000.00 US Dollar . USD Per annum

2021-12-03 08:50:53

Job location Accord, New York, United States

Job type: fulltime

Job industry: Banking & Financial Services

Job description

A bulge bracket investment bank is looking to further its presence in the US markets and is looking to add a machine learning expert to their overarching model risk function. This position would lead a small team that would oversee the validation and monitoring of various models across the enterprise assuring that machine learning/ boosting tools have been implemented properly while remaining compliant with federal banking requirements. While majority of the models you will be covering will focus on US Credit Card products, you will be lending support across the entire banking platform. Additionally, you will be responsible for dealing with federal regulators handling submissions for CCAR, CECL and other banking regulations.

Responsibilities

Effectively manage and train a team of quants (5-8 headcount; onshore & offshore headcount)

Stay up to date on all of the latest machine learning methodologies and tools to assure sound model performance.

Re-engineer existing models to optimize decision times and comply with federal regulatory guidelines.

Handle the end-to-end implementation, validation and reporting efforts for the entire MRM business unit.

Spearhead the banks transition to machine learning and artificial intelligence and servicing as a subject matter expert for the business.

Requirements

Masters; degree or above in any STEM related field of study.

10+ years of experience in the consumer banking or retail lending pace, specifically for credit card lending.

5+ years of experience managing a team of direct reports (Global scale is preferred but not required)

Expert proficiency with Python, R, SAS and other popular programing tools.

Exceptional communication skills are an absolute must as you will be working conjointly with multiple business lines.

Proven experience developing and implementing machine learning models is an absolute must.

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