U.S. Bank Fraud Data Analyst in Lansing, Michigan
The Fraud Data analyst is responsible for mapping data requirements definition to successful completion, including the discovery, analysis and documentation of data requirements, data and process flows, use cases, and test cases. The position will be the liaison between client subject matter experts, source data and development teams. The position will also apply delivery methodology standards in the creation of solutions, understanding client tactical plans and goals and expressing business requirements in terms of the function to be performed by the solution.
Individuals applying for this position will work closely with quality assurance, project management, vendors and technology teams. He/She is responsible for conducting analysis, defining the data requirements and data mapping expectations in conjunction with the Fraud BA lead/Product Owner. Understanding of the Actimize UDM or IFM data strategy is preferred. Experience mapping customer, account and transactional data is required. Experience with real time transactional solutions (ex: fraud, card) is also preferred. This is a team-based position that requires strong interpersonal skills.
-Bachelor's degree or equivalent work experience
-At least 7 years experience with developing and implementing applications.
-7 years Data Analysis experience
-3 plus years of structured SQL programming
-5 plus years of experience working on designing data models
-Experience working with large databases
Oracle RAC experience
Financial industry experience
Strong planning and organizational skills
Strong written and verbal communication skills
Job: Information Technology
Primary Location: Minnesota-MN-Richfield
Shift: 1st - Daytime
Average Hours Per Week: 40
Requisition ID: 180035686
Other Locations: United States
U.S. Bank is an Equal Opportunity Employer committed to creating a diverse workforce.
U.S. Bank is an equal opportunity employer committed to creating a diverse workforce. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, among other factors.