Corporate Data Analyst - Fraud AML

Overview

About The Role

This role will lead and manage the fraud and BSA/AML data and reporting capabilities while maintaining strong relationships with business leadership to achieve company and regulatory objectives. This role will support the modernization of fraud/AML processes and lead the usage of exploratory analytics and data automation to uncover insights with targeted and actionable recommendations from multisource datasets. Plays a critical role in extracting value from data, optimizing business processes, and driving competitive advantage through analytical techniques and data support.

This is a Corporate position which may be located at an available bank division location across our nine-state footprint in AZ, CO, , MT, NV, TX, UT, WA, or WY. The entry rate for this position is $69,464.94 + / per year (calculated for Kalispell, MT).

All compensation offers are analyzed individually and take into consideration multiple factors including but not limited to geographic location, years of experience, and educational background.

WA Applicants ONLY:
Range $75,663.06 to $ per year

• Reviews existing data and operational processes to identify best practices and opportunities for improvement.
• Creates interactive dashboards, reports, and tools to support FrAML processes and communicate findings.
• Identifies and supports process improvement and operational modernization efforts throughout the fraud/BSA/AML business unit.
• Performs in-depth statistical analysis using advanced statistical techniques and machine learning algorithms to support core business initiatives, including support of vendor-provided models and tools.
• Develops and maintains efficient, reusable data assets to support analytics and reporting efforts.
• Works with key business partners to understand business priorities, identify strategic initiatives, and develop effective and timely analytic solutions. Supports and aligns with broader Business Intelligence and Analytics priorities.
• Remains updated with the latest methodologies, tools, and industry trends in machine learning and artificial intelligence.
• Must comply with all company policies and procedures and all applicable laws and regulations, including but not limited to, the Bank Secrecy Act, the Patriot Act, and the Office of Foreign Assets Control. Must complete the assigned online training courses and achieve a passing score by due date.

Education

• Required — Bachelor’s Degree in economics, quantitative business analysis, applied mathematics, statistics, management information systems or equivalent combination of education and experience required.

Experience

• Required — Minimum of 3 years in financial services with a focus in fraud and/or BSA/AML analytics.
• Expert — Minimum of 3 years experience working with data as an analyst or engineer, with experience in visualization tools such as Tableau, Power
  
  BI, etc.
• Expert — Expert experience working with SQL and relational database systems.
• Beginner — Other statistical or analytics-related languages such as R, Python, Spark, or similar.
• Beginner — Experience in Data Modeling, Data Architecture, and Enterprise Data Governance Frameworks preferred, with a focus on Kimball-style dimensional data modelling.
• Advanced / Specialized Knowledge — MS Excel, PowerPoint, Word, and ability to create user-friendly technical reports.
• Preferred — Knowledge of Data Bricks or similar modern data warehousing and analytics platform.

Would an equivalent combination of relevant education and work experience be considered? Yes

License/Certification

• Required/Preferred: (no specific licenses listed in original description)

Required

Skills and Abilities

• The ability to motivate or influence internal or external senior level professionals is a critical part of the job, requiring influence and trust, and excellent written communication skills.
• Exceptional communication skills with the ability to talk to every level, from C-level executives to front-line employees.
• Knowledge of and experience working with complex databases.
• Ability to analyze data to discover hidden patterns and conduct error/deviation analysis.
• Curiosity about technology-driven solutions and…