Bachelor’s degree in mathematics, statistics, computer science, engineering, economics, finance, or a related quantitative discipline + 5+ years of relevant experience in quantitative analysis, risk management, or model lifecycle activities + Strong analytical skillset with demonstrated ability to translate complex data into business insights + Proficiency in data and analytical tools such as Python, SAS, SQL, Tableau (or similar) + Working knowledge of model risk management frameworks, including model development, validation, monitoring, and documentation + Understanding of credit and/or fraud risk strategies and underlying business drivers + Proven ability to operate effectively in cross-functional environments, influencing stakeholders across technical and non-technical teams + Excellent communication skills, including the ability to articulate complex concepts clearly and persuasively to senior audiences . The successful candidate will play a critical, highly visible role partnering with Global Risk Analytics (GRA), strategic vendor and Model Risk Management stakeholders as a key liaison and subject matter expert, providing business context, data insight, and analytical support to ensure effective and practical model governance.