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Credit Risk Modeler

ConfidentialChennai

6 days ago

Job description

Credit Risk Modeler / Quantitative Analyst

We are seeking a highly skilled and motivated individual with a strong understanding of predictive modeling techniques and their practical application. This role requires expertise in credit lifecycle statistics and machine learning techniques , coupled with robust programming and communication skills.

Required Qualifications :

Master's degree in Mathematics, Statistics, Economics, Engineering, or a related quantitative discipline, or a demonstrated track record of performance proving equivalent ability.
Very good understanding of Predictive modeling techniques and their application.
Knowledge of Credit life cycle Statistics and machine learning techniques.
Experience conducting and applying statistical methodologies including linear regression, logistic regression, ANOVA / ANCOVA, CHAID / CART, and cluster analysis.
Good understanding of Probability of Default (PD), LGD, and EAD modeling techniques.
Demonstrated knowledge in credit and / or market risk measurement and management.
Excellent problem-solving, communication, and data presentation skills.
Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly.
Proficiency in SAS, SQL, GCP, R, and PYTHON.
Fluency with Excel, PowerPoint, and Word.

Key Responsibilities :

Execute analytics special studies and ad hoc analyses.

Utilize SAS, GCP, R, and Python for model building and model validation.

Continuously enhance statistical techniques and their applications in solving business objectives.

Compile and analyze results from modeling output and translate them into actionable insights.

Prepare PowerPoint presentations and documentation for the entire credit risk modeling process.

Collaborate, support, advise, and guide in the development of models.

Acquire and share deep knowledge of data utilized by the team and its business partners.

Participate in global conference calls and meetings as needed, and manage multiple customer interfaces.

Evaluate new tools and technologies to improve analytical processes.

Set own priorities and timelines to accomplish projects, demonstrating accountability for project deliverables.

Skills Required

Market Risk, Logistic Regression, Anova, Sas, Analytical, Predictive Modeling, Python

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