Overall purpose of role
The VP role is responsible for the development, implementation support and ongoing maintenance of models for the Barclaycard UK portfolio. The model scope includes impairment, regulatory capital, stress testing, credit decision (e.g. underwriting) and risk-reward models.
About Quantitative Analytics
Quantitative Analytics (QA) is a global organisation of highly specialized quantitative modellers and developers. QA is led by Marco Naldi, who is a member of Risk Exco.
QA is responsible for developing, testing, implementing and supporting quantitative models for valuation and risk management of traded assets, regulatory and economic capital, impairments, scenario generation, fraud detection, asset-liability management, operational risk, net revenue and balance sheet forecasting, and stress testing across Barclays.
About QA BUK Retail Credit
QA BUK Retail Credit is responsible for the development and implementation support and maintenance of impairment, regulatory capital, planning, stress testing, credit decision and risk reward models for BUK.
BUK businesses comprise UK Cards, Mortgages, Unsecured Loans, Current Accounts, Business Banking and Wealth.
Work with stakeholders across functions, driving value by developing innovative modelling and analytical solutions for credit risk management.
Independently develop best-in-class models for use in the retail lending business, specifically for the market-leading Barclaycard UK, including calibrations of existing models and associated analytics.
Provide the business with insights and recommendations for strategy and process improvement.
Ensure that all models are compliant with internal and external requirements, including documentation standards.
Research statistical techniques and industry best practice for models.
Liaise with systems/infrastructure teams to user-test and implement models successfully.
Work closely with the QA Model Monitoring function to ensure that model performance is appropriately tracked.
Maintain awareness of the wider commercial environment and a good sense of business drivers affecting the Bank's balance sheet and P&L.
Liaise with Model Owners and other key stakeholders to continually improve models in use.
Contribute to building, shaping and developing a motivated and talented team, capable of delivering analytics of the highest calibre.
Participate in risk governance committees, e.g. the BUK Model Risk Committee, to explain the outcomes and benefits of modelling and analytical solutions using presentation skills, technical acumen, and knowledge of the wider business environment.
Stakeholder Management and Leadership
Support various stakeholders such as Risk, Finance and Product through analytical thought leadership and model development and deployment.
Strive to establish and maintain a reputation for strong, consistent and value-adding support among key model and analytics stakeholders.
Potentially take on direct line management responsibility for other team members, including direction, coaching and performance management.
Risk and Control Objective
Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays policies standards.
Passionate about data analytics and its commercial applications
Possessing a data-driven and results-orientated mind-set
A self-starter, able to work proactively and independently when needed
Resilient, overcoming challenges resourcefully and meeting timelines under pressure
Confident enough to challenge constructively where appropriate
Flexible enough to operate in a fast-paced, changing commercial and regulatory environment
A team player, willing to help others freely and to seek help when needed
Able to maintain good relationships with a variety of stakeholders across functions and geographic locations
A university degree or equivalent in statistics, mathematics, operations research or another quantitative area; or significant relevant industry experience
5+ years of relevant industry experience
Extensive experience in statistical model development, including capital and impairment models, with a track record of successful delivery
Full proficiency in advanced SAS programming and Excel manipulation
Good understanding of standard model risk controls throughout the development lifecycle, including best coding practice and clear documentation
Good communication, negotiation and influencing skills
Good understanding of retail banking products
Experience and familiarity with industry-standard retail credit risk decision modelling techniques
Up-to-date working knowledge of regulatory requirements relevant to UK models
Proficiency in analytical programming with Python