BSA Data Manager

The BSA Data Manager works closely with business partners to turn data into critical information and knowledge that can be used to make sound anti-money laundering (AML), sanctions, and fraud risk management decisions.  The individual must be detail oriented, able to manage multiple tasks, and lead data-driven changes. Also includes supporting AML, Sanctions, and Fraud systems, analyzing data, tuning applicable rules/parameters, selecting samples and making recommendations on system optimization.  This individual must also be able to analyze large amounts of raw and structured information to find patterns that will help our company. Works closely with Fraud strategy and BSA data analytics teams. We offer flexible Hybrid schedule.

• 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

• 7+ years hands on experience with ERM, KYC, BSA/AML, OFAC or other areas of Fraud.
• MS in Computer Science / Statistics / Operations Research / Business Analytics or equivalent combination of skills, experience and education
• Banking product
• experience
• Analytical mind and business acumen
• Experience using business intelligence tools (e.g. Power BI) and data frameworks (e.g. Hadoop)
• Creative problem solver who thrives when presented with a challenge
• Excellent pattern recognition and predictive modeling skills
• Experience with programming languages such as Python, R, .NET C#
• Excellent attention to detail
• Able to multitask, prioritize, and manage time effectively
• Excellent communication, presentation, interpersonal and organizational skills

Desired

• Experience with NICE AML and Fraud products is a plus
• Experience in a similar role at a financial institution or large consulting firm is a plus
• Software language - C#, Power Shell
• Experience working in Agile development environment