Director, Specialty Compliance and Ethics, Data Analytics - AI

The

Director of Data Analytics – AI

will lead the Emerging Technology pillar of our Analytics, Systems and Emerging Technology team. This role focuses on overseeing the responsible and effective deployment and maintenance of AI models within our financial services organization, ensuring they comply with both internal policies and external regulatory requirements. The ideal candidate will have a strong technical background, experience with AI models, and a proven track record of improving model performance without the extensive theoretical focus typical of a data scientist role. This position involves practical, hands-on work with models to develop, tune, calibrate, and maintain their efficacy and oversee their governance in real-world applications.What you’ll do….Identify and help deploy generative AI use cases for financial services complianceDevelop and refine financial services model governance frameworks to ensure all AI models are compliant with applicable BSA laws, regulations, and Walmart standards for AI modelsCollaborate with legal, digital citizenship, privacy, and technical teams to interpret regulations and translate them into operational requirements for AI models; keep abreast of changes in AI regulation and best practices, updating governance policies accordinglyConduct risk assessments for AI models to identify potential compliance and ethical risks; implement controls and mitigation strategies to manage identified risks; monitor compliance with governance frameworks and report on adherence and exceptionsPerform hands-on tuning and calibration of AI challenger models to meet specific performance metrics; optimize model parameters for efficiency, accuracy, and performance; document tuning processes, results, and decisions for transparency and compliance with industry standardsMonitor ongoing performance of champion challenger models in production, identifying degradation and opportunities for enhancementCollaborate with cross-functional teams including data engineers, AI researchers, and business stakeholders to understand requirements and integrate feedback; work closely with IT and Data Science teams to enhance data systems and tools for fraud detectionPresent findings and progress to technical and non-technical stakeholders in a clear and actionable manner; prepare reports for internal stakeholders and regulatory bodies as requiredWhat you’ll bring…Strong knowledge about model risk management and regulatory landscape affecting AI; a proven track record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML modelsExperience deploying AI models, particularly ML and LLM modelsStrong understanding of AI model architecture and the factors influencing model performanceProficient in SQL, Python, and BI platform such as Tableau Prep or DataikuExperience with machine learning frameworks (e.g., TensorFlow, PyTorch)Familiarity with cloud technologies and environments such as Azure, or Google CloudExperience using Quantexa, Featurespace and/or Actimize IFMX vendor platformsStrong analytical and problem-solving skills, with the ability to handle complex information and make decisionsExcellent communication skills and the ability to work collaboratively across team boundaries

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