Senior Fraud Risk Analyst
operates. **HOW YOU’LL MAKE A DIFFERENCE** + Proactively assists in the oversight of a proactive Fraud Risk Management Program using data extraction, data analytics and management reporting. + Extensive understanding of fraud risks, and risk management processes in order to identify and monitor fraud risks within the organization. + Contributes to the development and implementation of Fraud Risk processes, tools, policies, standards, and procedures in alignment with the Enterprise Risk Framework Program. + Analyzes activity to detect and prevent fraudulent activity based on reports, alerts, or notifications from third parties requesting assistance. + Analyzes all potential or actual fraud within the Bank, including, but not limited to: check, deposit, new account, card
VP, Data Platform Architect & Modeler
operates. **HOW YOU’LL MAKE A DIFFERENCE** + Data Modeling & Architecture + Design, build, and maintain conceptual, logical, and physical data models to support analytics, reporting, and operational workloads. + Ensure dimensional and relational data models support data warehousing and self-service analytics. + Develop and optimize data structures in Snowflake to ensure performance, scalability, and business alignment. + Utilize dbt to build and manage transformations for clean, structured, and reusable data models. + Conduct POCs to evaluate new tools, methodologies, and modeling techniques to improve performance, efficiency, and scalability + Establish and enforce data standards, governance, and best practices for data across the organization. + Ensure data models comply with regulatory, security, and compliance requirements. + Prototyping & Solution Exploration + Design and implement small-scale prototypes and evaluations to test approaches for data modeling, performance running, and architecture improvements. + Assess and compare data modeling techniques, integration strategies, and observability tools to recommend the best solutions for the enterprise. + Work closely with data engineering and analytics teams to assess new methodologies before full-scale implementation. + Document findings from evaluations and provide technical guidance on their adoption. + Data Observability, DataOps, & DevOps + Implement data observability tools to monitor data health, lineage, and anomalies across pipelines. + Integrate DataOps principles to automate data quality checks, validation, and governance processes. + Work with DevOps teams to ensure CI/CD pipelines support automated deployments and version control for data models. + Define and enforce data validation, monitoring, and alerting mechanisms to proactively address