Senior Fraud Analytics & Strategy Analyst, Global Payments

Bank of America; United States; On-site; USD 85,000 - 135,000; Full time

Job summary

Bank of America is seeking a data analyst to perform complex analysis and modeling to minimize loss exposure and improve customer experience. The role uses Excel, SAS, SQL, Tableau and other databases to provide analytical support, evaluate data for fraud risk and propose policy changes within segmentation structures.

The ideal candidate will have SQL/SAS experience, familiarity with AI concepts, and a background in data analytics to support diverse fraud mitigation initiatives across projects.

Qualifications

• Bachelor's degree or equivalent experience in CS/Data Management/Statistics.
• 1+ years experience in SQL/SAS.
• Intermediate SQL knowledge; familiarity with TOAD and SQL Server.
• Awareness of AI / ML concepts and ability to apply strategies.
• Experience in data analytics and interpreting large data sets.
• Scripting experience with Python, Java, VB, or SAS.

Responsibilities

• Develop and update business rules to minimize false-positive fraud alerts.
• Coordinate with multiple projects and capture requirements for data needs.
• Analyze alerts daily and craft strategies using pattern matching and trends.
• Query and analyze data for ad hoc requests and generate team reports.
• Collaborate with Tech teams to test and implement process improvements.
• Ensure data accuracy, completeness, and quality controls.

Skills

SQL

SAS

Python

Data analytics

Data interpretation

AI concepts

Education

Bachelor's degree in CS/Data Management/Statistics

Tools

TOAD

SQL Server

Job description

Bank of America is seeking a data analyst to perform complex analysis and modeling to minimize loss exposure and improve customer experience. The role uses Excel, SAS, SQL, Tableau and other databases to provide analytical support, evaluate data for fraud risk and propose policy changes within segmentation structures.

The ideal candidate will have SQL/SAS experience, familiarity with AI concepts, and a background in data analytics to support diverse fraud mitigation initiatives across projects.