Modelling Analyst

The role is accountable for the Modelling Unit through overseeing the development and enhancement of quantitative models, methodologies, analysis, and related software tools in line with internal policies, regulatory standards and international best practice.

• Personal Attributes and Experience
• Excellent written, verbal, and interpersonal communication Skills, including the ability to communicate technical concepts to a non
• technical audience.
• Proven statistical modelling, forecasting and analytical Experience.
• Ability to articulate key messages and analysis outcomes clearly and concisely with a Pragmatic and analytical mind.
• Ability to operate autonomously and under minimal supervision, operate as a self
• motivated, pro
• active, and result
• driven problem solver with excellent analytical Skills as well as be an effective member of a broader team.
• Experience in the financial services industry in a quantitative field (model development /review, risk modelling, analytics or quantitative research) covering applied statistics, data manipulation, programming and analytical techniques such as linear and nonlinear regression, time series forecasting, panel data analysis, optimisation, data mining and survival analysis,
• Proficiency in programming and data analytics tools Skills such as Python, R, SAS, SQL and Machine Learning for large date sets.
• Knowledge and Experience of the model development process and international best practices.
• Knowledge of Basel II/ III, and IFRS 9 Requirements is a must.

• Lead and oversee the development of models (that is, design, estimate, implement, test, document and maintain quantitative models), whilst ensuring that adequate documentation and controls are maintained for all models and methodologies to enhance decision making within CABS.
• Lead the model review and testing program, to periodically review model performance, within a given framework, and recommend changes to the models. Develop model performance metrics and perform ongoing monitoring.
• Provide accurate and timely financial modelling advice to the business in a way that non
• specialists can easily understand.
• Ensure adherence to model risk management policies, procedures, and processes.
• Champion data quality and integrity by highlighting data quality issues and suggesting appropriate solutions.
• Development, testing, documentation and maintenance of the Society’s models and analytical tools using the appropriate methodologies to meet standards set by the model governance policies.
• Share knowledge and Experience on analytics and modelling best practices as well as mentoring and development of the modelling team Skills and Skills.
• Work closely and effectively with colleagues in the business to understand the business context for model use, producing technical guidance and adding value to the business process.

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