Note: When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.
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Looking for SG5/SG6 candidates.
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3+ years of experience in Credit Risk Analytics or Model Implementation.
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Strong programming experience in Base SAS and SAS Enterprise Guide.
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Good understanding of credit risk modelling concepts, model implementation pipeline, risk scoring process, IFRS9/CECL concepts, including PD, LGD, EAD, and ECL.
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Experience with SQL, data validation, testing, impact analysis and production support.
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Knowledge of Model Risk Management / Model Governance frameworks and practices. • Working knowledge of the Linux environment.
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Exposure to Python, Google Cloud Platform (GCP), or automation tools is an added advantage.
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Exposure to AI/LLM model usage is an added advantage.
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Exposure to Banking or Non-Banking Financial Lending is an added advantage.
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Implement, validate, test, and Productionalize predictive models and risk strategies across global platforms.
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Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.
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Implement and maintain credit risk models (Scorecard models, PD, LGD, other risk models) using SAS.
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Perform code development, testing, reconciliation, and production deployment for model enhancements and business logic changes.
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Support production execution and impact analysis and resolve implementation issues within agreed timelines.
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Collaborate with Model Development, IT, and business stakeholders to implement model enhancements and change requests.
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Prepare technical and workflow/process documentation and support internal and external audits.
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Drive automation and continuous process improvements by proactively identifying opportunities to enhance operational efficiency.
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Identify opportunities to introduce automation, GenAI tooling, and workflow simplification and develop Proof-of-Concepts, and enhance delivery processes through automation.
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Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.
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Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, or related field required.
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Strong analytical, critical thinking, and problem-solving abilities.
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Strong ownership mindset with accountability for deliverables.
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Ability to learn new tools and technologies quickly.
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Excellent interpersonal and communication skills.
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Ability to work independently with minimal supervision.
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Proactive, curious, and willing to ask questions to uncover opportunities.
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Commitment to building efficient, scalable, and high-quality analytics solutions.
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Attention to detail with a commitment to delivering high-quality solutions.
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Flexible and adaptable, able to take on diverse responsibilities while consistently meeting delivery timelines to the highest quality standards.
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Ability to collaborate effectively in a global, cross-functional environment.
