Senior Data Analyst
3 weeks ago
- Develop, review, and enhance credit risk identification, assessment, monitoring, reporting, and management methodologies, policies, and processes in compliance with regulations, internal policy, and external stakeholders.
- Plan and monitor credit risk portfolios and align credit risk with the organization's business strategy.
- Keep abreast of the latest financial risk management techniques and industry best practices.
- Work closely with cross-functional teams on various projects as needed.
- Provide regular credit risk reports to senior management and Board members, especially the Company's Credit & Risk Committee, detailing identified risks and action plans.
- Define and monitor credit risk limits, recommend action plans if limits are breached, and support formulating credit risk-adjusted prices for relevant credit products.
- Implement and review credit risk measurement methodologies.
- Lead and ensure setup of model methodology, credit data collection, build up and monitoring of credit models (e.g., scorecards, probability of default).
- Propose and implement credit analysis, monitoring, and early warning triggers for proactive credit portfolio management.
- Prepare reporting materials and ensure data integrity, including special reports (as needed).
- Degree should reflect strong math background.
- Should have credit risk background.
- Should have strong SQL skills.
- Experience in statistical analysis.
- Graduate of any course related to business management and/or statistics/mathematics. An advanced degree or certification such as FRM or CRM is highly desirable.
- At least eight (8) years of relevant credit risk management experience from the financial industry.
- Experience in working with a lending company for consumer loans/personal loans is a must.
- Strong experience and understanding of finance, banking business, and handling consumer (Retail, MSME) lending (secured and unsecured) credit risk and portfolio management.
- Experience and/or familiarity with data and statistical software/tools – i.e., SAS, SQL, R Studio, Python, and the like.
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