Wissen Technology is hiring forLead IRB Credit Modelling
About Wissen Technology:
At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this Through a combination of deep domain knowledge, cutting-edge technology expertise , and a relentless focus on quality. We don't just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives . We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent . Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
Job Summary: We are seeking an experienced Lead IRB Credit Modelling professional (12–17 years) to drive the develop ment, validation, and governance of credit risk models across retail and wholesale portfolios. This role focuses on building and refining IRB parameters (PD, LGD, EAD) in line with UK PRA Basel 3.1 regulatory standards . The ideal candidate will bring strong quantitative expertise , hands ‑ on modelling experience, and the ability to engage with business and ri sk stakeholders to ensure effec tive use o f models within the credit risk framework.
Experience: 1 2 - 17 Years
Location: Mumbai
Mode of Work: Hybrid
Key Responsibilities:
- Develop and refineIRB credit risk models(PD, LGD, EAD, slotting models).
- Lead end ‑ to ‑ endmodel lifecycle managementincluding scoping, data analysis, development, validation, and governance approvals.
- Conductmodel performance analysis, including calibration, backtesting , and annual model reviews.
- Identifyand resolve model deficiencies and improve model robustness.
- Ensure modelscomply withUK PRA Basel 3.1 IRB standardsand regulatory requirements.
- Research and implement best practices incredit risk modelling methodologies.
- Collaborate with Credit, Risk, and business teams to ensure effective model usage and interpretation.
- Prepare high ‑ qualitydocumentation, model reports, and regulatory submissions.
- Communicate analysis, findings, and recommendations effectively to both technical and non ‑ technical stakeholders.
Required Skills And Qualification
- 12–17 years of experience incredit risk modellingwith strong focus on IRB frameworks.
- Hands-on experience developingPD, LGD, EAD modelsfor retail or wholesale portfolios.
- Strong knowledge ofBasel regulations, particularlyUK PRA IRB standards(EBA exposure is acceptable).
- Strong academic background inquantitative fields(Mathematics, Physics, Engineering, Economics, etc.).
- ProficiencyinSQL and/or Pythonfor data analysis and modelling.
- Strong analytical and statistical modelling skills .
- Experience managingmodel development and validation lifecycle.
- Excellent communication and documentation skills.
- Ability to work independently and lead initiatives while collaborating with stakeholders.
Good To Have Skills
- Experience leading teams or acting as aproject/team leadin modelling initiatives.
- Experience withmortgage or wholesale credit portfolios.
- Familiarity withregulatory interactions, model governance, and audit processes.
- Exposure to advanced modelling techniques or machine learning in credit risk.
- Experience working in global financial institutions or regulated environments.
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Website: www.wissen.com
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Wissen Thought Leadership: https://www.wissen.com/articles/
