Credit Risk Data Scientist

As a Credit Data Scientist, your role involves developing and validating credit risk models, enhancing the usage of Artificial Intelligence/Machine Learning to create more efficient solutions, and utilizing tools like GCP, SAS, R, and Python for model building and validation. You will continually enhance statistical techniques to achieve business objectives and translate modeling results into actionable insights. Your responsibilities will also include preparing presentations and documents, collaborating with team members, supporting model development, and acquiring and sharing deep knowledge of data. Key Responsibilities: - Master's degree in Finance, Financial Engineering, Analytics, Mathematics, Computer Science, Statistics, Industrial Engineering, Operations Research, or related field - Good understanding of Probability of Default (PD), LGD, and EAD modeling techniques - Hands-on experience in Artificial Intelligence, with extensive experience in GCP - Strong understanding of predictive modeling techniques and their applications - Knowledge of the credit life cycle and statistics/machine learning techniques - Proficiency in statistical methodologies like linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, and cluster analysis - Proficient in programming with GCP, R, SAS, and Python - Fluency in Excel, PowerPoint, and Word - Excellent written and oral communication skills for conveying complex information clearly - Experience in developing and implementing cloud-based analytical solutions - Ability to set priorities and timelines for project deliverables - Practical applications of mathematical modeling and Artificial Intelligence - Demonstrated knowledge in credit and/or market risk measurement and management Qualifications Required: - Senior-level experience in a similar role - Master's degree in Mathematics, Statistics, Economics, Engineering, or related discipline - Problem-solving skills, effective communication, and data presentation abilities - Proficiency in GCP, SAS, SQL, and Python Please note that the company's additional details were not provided in the job description. As a Credit Data Scientist, your role involves developing and validating credit risk models, enhancing the usage of Artificial Intelligence/Machine Learning to create more efficient solutions, and utilizing tools like GCP, SAS, R, and Python for model building and validation. You will continually enhance statistical techniques to achieve business objectives and translate modeling results into actionable insights. Your responsibilities will also include preparing presentations and documents, collaborating with team members, supporting model development, and acquiring and sharing deep knowledge of data. Key Responsibilities: - Master's degree in Finance, Financial Engineering, Analytics, Mathematics, Computer Science, Statistics, Industrial Engineering, Operations Research, or related field - Good understanding of Probability of Default (PD), LGD, and EAD modeling techniques - Hands-on experience in Artificial Intelligence, with extensive experience in GCP - Strong understanding of predictive modeling techniques and their applications - Knowledge of the credit life cycle and statistics/machine learning techniques - Proficiency in statistical methodologies like linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, and cluster analysis - Proficient in programming with GCP, R, SAS, and Python - Fluency in Excel, PowerPoint, and Word - Excellent written and oral communication skills for conveying complex information clearly - Experience in developing and implementing cloud-based analytical solutions - Ability to set priorities and timelines for project deliverables - Practical applications of mathematical modeling and Artificial Intelligence - Demonstrated knowledge in credit and/or market risk measurement and management Qualifications Required: - Senior-level experience in a similar role - Master's degree in Mathematics, Statistics, Economics, Engineering, or related discipline - Problem-solving skills, effective communication, and data presentation abilities - Proficiency in GCP, SAS, SQL, and Python Please note that the company's additional details were not provided in the job description.