Credit Risk Modeler

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  Location

  (INDIA) and Chennai

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  Job Reference

  21746

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  Functional Area/Experience

  Business, Accounting & Finance / Fresh Graduate

Job Description & Qualifications

Job Category: Global Data Insight & Analytics

• Very good understanding of Predictive modeling techniques and their application.
• Knowledge of Credit life cycle
• Statistics and machine learning techniques.
• Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis.
• Good understanding of Probability of Default (PD), LGD and EAD modeling technique.
• Team player and collaboration skills.
• Programming skills in SAS, GCP, R and PYTHON.
• Fluency with Excel, PowerPoint and Word
• Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly

Responsibilities

• Develop and validate credit risk models
• Execute analytics special studies and ad hoc analyses
• Using SAS, GCP, R, Python for model building and model validation
• Continual enhancement of statistical techniques and their applications in solving business objectives
• Compile and analyze the results from modeling output and translate into actionable insights
• Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process
• Collaborate, Support, Advise and Guide in development of the 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 (accountability for project deliverables)

Qualifications

• Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline or a track record of performance that demonstrate this ability
• Practical applications of mathematical modeling, Operations Research and Machine Learning techniques
• Demonstrated knowledge in credit and/or market risk measurement and management
• Excellent problem solving, communication, and data presentation skills
• Proficient with SAS, SQL and GCP

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