Reference: CFA020978-KR-1
Are you a numbersdriven thinker with a passion for analytics modelling and innovation Were looking for a Quantitative Analyst who loves solving complex problems developing cuttingedge models and turning data into strategic insights. If you thrive in a space where machine learning meets credit risk while keeping things collaborative and engaging wed love to connect with you!
Duties & Responsibilities
Leadership and Collaboration:
Contribute positively to team culture and continuous learning
Collaborate with senior analysts and crossfunctional teams to support strategic credit initiatives
Demonstrate analytical curiosity and play an active role in innovation across the function
Support a highperformance culture consistent with organisational values
Share knowledge best practices and insights to uplift the wider analytics community
Technical & Analytical Responsibilities:
Develop and maintain advanced analytics frameworks for credit portfolio management
Apply machine learning and advanced statistical techniques to enhance predictive accuracy and decisionmaking
Conduct deepdive portfolio analysis including RWA and Economic Capital attribution and optimisation
Build dashboards and visualisation tools for realtime portfolio monitoring
Integrate analytics into strategic planning and risk appetite frameworks
Skills & Experience:
Minimum 2 years experience in credit risk analytics quantitative modelling or related functions
Strong proficiency in SAS Python R SQL
Exposure to IFRS9 Basel frameworks and credit modelling techniques
Strong analytical and problemsolving capability
Excellent communication and stakeholder engagement
Ability to work independently and collaboratively within a highperforming team
Qualifications:
Degree in Mathematics Statistics Financial Engineering Actuarial Science Economics or another quantitative discipline
Postgraduate studies or certifications in Data Science Machine Learning FRM or CFA is advantageous
Contact:
Kayla Reddy
Connect With Us: Visit and Register Your CV to explore all our Finance Risk and Analytics vacancies.
If you do not receive feedback within two weeks please consider your application unsuccessful. Your profile will be stored for future opportunities.Required Experience:
IC
Reference: CFA020978-KR-1Are you a numbersdriven thinker with a passion for analytics modelling and innovation Were looking for a Quantitative Analyst who loves solving complex problems developing cuttingedge models and turning data into strategic insights. If you thrive in a space where machine lea...
Reference: CFA020978-KR-1
Are you a numbersdriven thinker with a passion for analytics modelling and innovation Were looking for a Quantitative Analyst who loves solving complex problems developing cuttingedge models and turning data into strategic insights. If you thrive in a space where machine learning meets credit risk while keeping things collaborative and engaging wed love to connect with you!
Duties & Responsibilities
Leadership and Collaboration:
Contribute positively to team culture and continuous learning
Collaborate with senior analysts and crossfunctional teams to support strategic credit initiatives
Demonstrate analytical curiosity and play an active role in innovation across the function
Support a highperformance culture consistent with organisational values
Share knowledge best practices and insights to uplift the wider analytics community
Technical & Analytical Responsibilities:
Develop and maintain advanced analytics frameworks for credit portfolio management
Apply machine learning and advanced statistical techniques to enhance predictive accuracy and decisionmaking
Conduct deepdive portfolio analysis including RWA and Economic Capital attribution and optimisation
Build dashboards and visualisation tools for realtime portfolio monitoring
Integrate analytics into strategic planning and risk appetite frameworks
Skills & Experience:
Minimum 2 years experience in credit risk analytics quantitative modelling or related functions
Strong proficiency in SAS Python R SQL
Exposure to IFRS9 Basel frameworks and credit modelling techniques
Strong analytical and problemsolving capability
Excellent communication and stakeholder engagement
Ability to work independently and collaboratively within a highperforming team
Qualifications:
Degree in Mathematics Statistics Financial Engineering Actuarial Science Economics or another quantitative discipline
Postgraduate studies or certifications in Data Science Machine Learning FRM or CFA is advantageous
Contact:
Kayla Reddy
Connect With Us: Visit and Register Your CV to explore all our Finance Risk and Analytics vacancies.
If you do not receive feedback within two weeks please consider your application unsuccessful. Your profile will be stored for future opportunities.Required Experience:
IC
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