Cynet Systems
SAS Fraud Analyst
Cynet Systems, Atlanta, Georgia, United States, 30383
Job Description:
Responsibilities:
Conduct analysis of data using SAS software to identify fraudulent activity and patterns. Investigate and report on potential fraud cases, including reviewing transactions, customer behavior, and other relevant data sources. Collaborate with cross-functional teams to develop and implement fraud prevention strategies. Monitor fraud-related KPIs and provide regular reporting on trends and patterns to key stakeholders. Identify new and emerging fraud risks and recommend proactive measures to mitigate these risks. Conduct ad-hoc analysis and data mining exercises to support fraud investigations and other business needs. Stay up to date on industry best practices and emerging trends related to fraud detection and prevention. Requirements:
Bachelor's degree in a related field, such as Statistics, Mathematics, Computer Science, or a related discipline. Minimum of 3 years of experience in SAS Fraud Analytics. Strong analytical skills and the ability to identify patterns and trends in complex data sets. Knowledge of fraud prevention tools and techniques. Excellent communication and interpersonal skills, with the ability to collaborate with cross-functional teams and present findings to key stakeholders. Strong attention to detail and the ability to prioritize and manage multiple projects simultaneously. Experience with SQL and other programming languages is a plus.
Responsibilities:
Conduct analysis of data using SAS software to identify fraudulent activity and patterns. Investigate and report on potential fraud cases, including reviewing transactions, customer behavior, and other relevant data sources. Collaborate with cross-functional teams to develop and implement fraud prevention strategies. Monitor fraud-related KPIs and provide regular reporting on trends and patterns to key stakeholders. Identify new and emerging fraud risks and recommend proactive measures to mitigate these risks. Conduct ad-hoc analysis and data mining exercises to support fraud investigations and other business needs. Stay up to date on industry best practices and emerging trends related to fraud detection and prevention. Requirements:
Bachelor's degree in a related field, such as Statistics, Mathematics, Computer Science, or a related discipline. Minimum of 3 years of experience in SAS Fraud Analytics. Strong analytical skills and the ability to identify patterns and trends in complex data sets. Knowledge of fraud prevention tools and techniques. Excellent communication and interpersonal skills, with the ability to collaborate with cross-functional teams and present findings to key stakeholders. Strong attention to detail and the ability to prioritize and manage multiple projects simultaneously. Experience with SQL and other programming languages is a plus.