Commercial bank located in San Francisco looking to bring on board a "Financial Crimes Compliance Data Manager" to join their team. The role is a full time opportunity, currently on a hybrid schedule (3 days in office / week).

Responsibilities:

• Responsible for complex data analysis efforts to discover patterns in large sets of data.
• Work closely with business partners and conduct analyses to translate data into actionable analytical solutions and promote information-based decision-making recommendations.
• Communicate results and ideas to key decision makers using data visualization techniques
• Coordinate and conduct the tuning and optimization of the various fraud, sanctions, and AML models based on the methodology established.
• Make recommendations to improve financial monitoring through the development of new risk models, statistical analysis of model thresholds, and other sensitivity and productivity analyses.
• Generate, monitor and update machine learning models used to identify fraudulent/suspicious activity or enhance productivity.
• Work with AML and Fraud teams to identify new models to assist in the identification of fraudulent/suspicious behavior or to enhance productivity.
• Use advanced statistical methods like clustering and regression analysis to ensure appropriate rigor around optimization processes.
• Conceptualize and develop new rules/models/scenarios, in coordination with Fraud, Sanctions, or AML subject matter experts, to address emerging trends and red flags.
• Ensure sound risk coverage, adequate quantitative model assessment and validation, and data quality completeness and integrity.
• Develop data-driven insights and communicate these effectively to management and diverse stakeholders, including management and regulators, using visualization techniques to showcase the results of analysis in concise presentations.
• Support business lines’ periodic risk assessments through the analysis of data elements related to potential indicators of customer, product, or geographic risk, evaluating and enhancing the Group's risk rating methodologies, and identifying new quantitative factors that can be incorporated into risk assessment processes.
• Support Model Risk Management's model validation efforts to ensure models are performing as intended.
• Keep up-to-date with latest technology trends