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Credit Data Science Manager II at Jobgether. This position is posted by Jobgether on behalf of Coastal Community Bank. We are currently looking for a Credit Data Science Manager II in the United States.. We are seeking an experienced Credit Data Science Manager II to lead the design, development, and oversight of credit risk models that drive decision-making, forecasting, and regulatory compliance. This role offers the opportunity to blend advanced data science expertise with business strategy, shaping portfolio performance and strengthening risk management practices. You will work closely with cross-functional teams and stakeholders, providing technical leadership while ensuring models align with organizational objectives and regulatory standards. This is a high-impact position, ideal for professionals who thrive in innovative environments and want to contribute to scalable, data-driven financial solutions.. . Accountabilities:. . Oversee the development, validation, and performance monitoring of credit risk models used for decision-making, forecasting, and regulatory reporting.. . Apply advanced statistical, econometric, and machine learning methods to credit loss forecasting and credit decisioning.. . Manage model governance frameworks, ensuring compliance with regulatory requirements and internal standards.. . Provide leadership in stress testing, CECL implementation, scenario analysis, and loss forecasting methodologies.. . Ensure data integrity, quality, and management of inputs/outputs for all models.. . Collaborate with stakeholders, regulators, and auditors to present model results and provide insights.. . Develop and implement policies and procedures for monitoring and validating models while aligning with strategic goals.. . Lead projects from planning through execution, ensuring effective reporting and follow-up on action plans.. . . Bachelor’s degree in Quantitative Finance, Economics, Statistics, Mathematics, Data Science, Computer Science, or related field (Master’s degree preferred).. . 7+ years of experience in credit risk modeling, model development, validation, or risk management.. . Proven expertise in Expected Loss modeling (PD, LGD, EAD) and experience with CECL, CCAR, DFAST, or IFRS 9 frameworks.. . Proficiency with statistical and programming tools such as Python, R, SAS, or SQL.. . Strong background in consumer credit products, including credit cards, loans, and unsecured lending.. . Familiarity with machine learning and statistical techniques for scorecards and origination underwriting models.. . Experience in modeling oversight, governance, or validation functions within banking, consulting, or financial services.. . Strong analytical, problem-solving, and communication skills, with the ability to present to both technical and non-technical stakeholders.. . Ability to thrive in a dynamic, fast-paced environment with strong leadership and team collaboration skills.. . . Company Location: United States.