Credit risk Modelling
1 month ago
Join EXL's innovative data science and engineering team, where we harness the power of generative AI to push the boundaries of data-driven solutions. At EXL, we're committed to exploring new frontiers in technology, and we need your expertise to drive us forward.
Join our team and immerse yourself in a collaborative environment, where together we'll tackle complex challenges, solve impactful problems for our clients and redefine the art of possibility leveraging data science.
Key Responsibilities:
- Develop and implement credit risk models using Python to predict default risk, probability of default (PD), loss given default (LGD), and exposure at default (EAD).
- Utilize statistical and machine learning techniques to build, validate, and improve models for assessing credit risk.
- Perform data extraction, transformation, and analysis using Python and SQL to support model development and testing.
- Collaborate with risk management teams to provide insights on model outcomes and their impact on business decisions.
- Ensure models comply with regulatory requirements and industry best practices.
Required Skills:
- Strong proficiency in Python for model development, machine learning, and data analysis.
- SQL expertise: Querying and handling large datasets.
- Experience with credit risk modeling: Probability of default (PD), loss given default (LGD), and stress testing.
- Strong knowledge of statistical modeling techniques (e.g., regression, decision trees).
- Excellent analytical and problem-solving skills.
Preferred Qualifications:
- Bachelor's or Master's degree in Data Science, Statistics, Finance, or a related field.
- Prior experience in credit risk modeling or the banking/finance industry.
- Familiarity with regulatory frameworks (e.g., Basel, IFRS 9).
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