Credit Risk Modeler

• 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

• 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)

• 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