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Senior Analyst

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

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