Responsibilities
**
- Design, develop, and maintain credit risk models across the credit lifecycle including acquisition, underwriting, portfolio monitoring, and loss forecasting.
- Apply statistical and analytical techniques to solve complex credit risk problems across banking portfolios.
- Leverage GenAI and LLMs, including prompt engineering, to support risk analysis, automation, documentation, and insight generation.
- Work closely with business and risk stakeholders to understand requirements and translate them into implementable analytical and GenAI-based solutions.
- Develop, validate, and document credit risk models in line with regulatory and internal governance standards.
- Support credit risk strategy initiatives such as scorecard development, policy analytics, segmentation, and portfolio optimization.
- Communicate analytical insights, model results, and GenAI outputs clearly to both technical and non-technical audiences.
- Provide technical guidance and mentorship to junior team members.
**Required Qualifications, Capabilities, and Skills:**
- Postgraduate degree in Economics, Statistics, Mathematics, Data Science, or a related quantitative discipline.
- 5+ years of experience in Credit Risk analytics or modeling within the banking or financial services domain.
- Strong understanding of credit risk concepts including PD, LGD, EAD, underwriting, scorecards, and portfolio risk.
- Hands-on experience with Python and SQL for data extraction, modeling, and analytics.
- Practical understanding of Generative AI / LLMs, including prompting techniques and applied business use cases.
- Strong communication and stakeholder management skills, with the ability to engage business, risk, and technology partners.
- Strong problem-solving mindset with the ability to structure ambiguous business problems.
**Desired Experience:**
- Experience in AML, Fraud, or Risk analytics within a banking environment.
- Exposure to regulatory frameworks such as Basel, IFRS9, CECL, or model risk governance.
- Experience integrating traditional credit risk models with GenAI-driven workflows.
- Prior experience in a consulting or client-facing analytics role.
**Desirable Skills:**
- Experience deploying analytics or GenAI solutions into production environments.
- Ability to translate complex analytical concepts into clear, actionable business recommendations.
- Strong ownership, leadership mindset, and ability to drive initiatives end-to-end.
- Curiosity and continuous learning attitude, especially in evolving AI and risk analytics areas. As a Gen AI Credit Risk Analyst and Modeler at Tiger Analytics, you will play a vital role in the Banking and Financial Services practice within the Credit Risk team. Your expertise in credit risk domain and hands-on analytical skills will be crucial in leveraging Generative AI and Large Language Models (LLMs) to enhance credit risk analysis, automation, and decision-support workflows. Your collaboration with business, risk, and compliance stakeholders will be essential in translating complex credit risk requirements into scalable analytical and GenAI-enabled solutions.
**
Responsibilities
**
- Design, develop, and maintain credit risk models across the credit lifecycle including acquisition, underwriting, portfolio monitoring, and loss forecasting.
- Apply statistical and analytical techniques to solve complex credit risk problems across banking portfolios.
- Leverage GenAI and LLMs, including prompt engineering, to support risk analysis, automation, documentation, and insight generation.
- Work closely with business and risk stakeholders to understand requirements and translate them into implementable analytical and GenAI-based solutions.
- Develop, validate, and document credit risk models in line with regulatory and internal governance standards.
- Support credit risk strategy initiatives such as scorecard development, policy analytics, segmentation, and portfolio optimization.
- Communicate analytical insights, model results, and GenAI outputs clearly to both technical and non-technical audiences.
- Provide technical guidance and mentorship to junior team members.
**Required Qualifications, Capabilities, and Skills:**
- Postgraduate degree in Economics, Statistics, Mathematics, Data Science, or a related quantitative discipline.
- 5+ years of experience in Credit Risk analytics or modeling within the banking or financ
