Assistant VP, Quantitative Risk Analyst

Barclays•New York, NY

1d•Hybrid

About The Position

The Assistant VP, Quantitative Risk Analyst role is responsible for designing, developing, implementing, and supporting mathematical, statistical, and machine learning models and analytics used in business decision-making. This includes developing predictive models, statistical analyses, optimization procedures, monitoring processes, data quality analyses, and score implementations for regulatory, impairment, and decision models. The role involves implementing models in Python-based Barclays Model Execution Framework (MEF) and Model Execution Service (MES) production environments, participating in overall project design and delivery, and producing robust documentation to fulfill governance requirements. The position also requires providing support for model development and implementation audits and ensuring project completion within agreed timeframes with end-client satisfaction. This is a hybrid role, with the possibility of telecommuting.

Requirements

Domain expertise
Experience with mathematical, statistical, and machine learning models and analytics
Experience with Python
Experience with Barclays Model Execution Framework (MEF)
Experience with Model Execution Service (MES)
Experience in project design and delivery
Experience producing robust documentation
Experience supporting audits of model development and implementation
Ability to work constructively with other Barclays resources
Ability to ensure project completion within agreed time frames
Ability to ensure end-client satisfaction
Barclays Values: Respect, Integrity, Service, Excellence and Stewardship
Barclays Mindset: Empower, Challenge and Drive

Nice To Haves

Leadership responsibilities
Experience advising and influencing decision making
Experience contributing to policy development
Experience taking responsibility for operational effectiveness
Experience collaborating closely with other functions/ business divisions
Experience leading a team performing complex tasks
Experience setting objectives and coaching employees
Experience appraising performance
Experience determining reward outcomes
Experience leading collaborative assignments
Experience guiding team members through structured assignments
Experience identifying the need for the inclusion of other areas of specialisation
Experience identifying new directions for assignments and/or projects
Experience identifying a combination of cross functional methodologies or practices
Experience consulting on complex issues
Experience providing advice to People Leaders
Experience identifying ways to mitigate risk
Experience developing new policies/procedures
Experience managing risk and strengthening controls
Experience performing work closely related to that of other areas
Experience collaborating with other areas of work, for business aligned support areas
Experience engaging in complex analysis of data from multiple sources of information, internal and external sources
Experience solving problems creatively and effectively
Experience communicating complex information
Experience influencing or convincing stakeholders to achieve outcomes

Responsibilities

Design analytics and modelling solutions to complex business problems using domain expertise.
Collaborate with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
Develop high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
Implement analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
Provide ongoing support for the continued effectiveness of analytics and modelling solutions to users.
Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
Ensure all development activities are undertaken within the defined control environment.
Develop predictive models, statistical analyses, optimization procedures, monitoring processes, data quality analyses, and score implementations supporting regulatory, impairment and decision models.
Implement models in python based Barclays Model Execution Framework (MEF) and Model Execution Service (MES) production environments.
Participate in overall project design and delivery with QA’s other functional teams and end-clients.
Produce robust documentation to ensure replicability of results and fulfill Barclays governance requirements.
Provide support for audits of model development and implementation, by both internal and external auditors working constructively with other Barclays resources to deliver projects.
Work with other QA staff to ensure project completion within agreed time frames and end-client satisfaction.