Understand and optimize Credit abuse risk management by analyzing trends in the data
Hands on experience with Data analytics and ability to lead the analysis into actionable business solutions
Perform Transaction, payment level analytics to make informed decisions impacting Credit Abuse
Strong quantitative aptitude and advanced skills in Excel, SAS, SQL and/or other analytical/data mining tools. Experience with a modeling package such as SAS E Miner is a plus.
Understand underlying business policies, operational processes and how these can be exploited by credit abusers
Analyze, understand and summarize the business problem and proposed solution for senior management
Qualifications:
2-4 years of experience in credit card risk management or equivalent experience preferably in financial services industry
Good business acumen and the ability to connect analytics with business decisions.
Proven ability to apply credit risk principles to achieve business priorities
Team player and comfortable presenting work to peers, cross functional businesses & senior management.
Collaborate closely with internal risk team, operations, fraud, execution
Demonstrated analytical, interpersonal and organizational skills
Education:
Bachelors Degree is required in Statistics, Mathematics, Economics, Engineering or a similar quantitative discipline with related work experience or Master's degree preferred