Credit Risk Technologist I

Position Summary   The Risk Technologist will ensure that we build and deliver the highest quality custom reporting solutions to support the risk team and improve program profitability. This will include diagnosing data issues and delivering solutions to support complex analytics. Additionally, the individual will be performing deep dive analysis and ad hoc analyses as needed, and identifying opportunities to improve the data structure and availability to better support decision making.   Essential Job Functions: May perform analysis for a wide range of requests using data in different formats from a variety of platforms Develop and maintain custom reporting solutions using T-SQL, SAS, and Microsoft tools such as Excel Develop best practices for report creation and deployments Maintain a working knowledge of Business Intelligence tools and follow best practices Participate in work stream planning process including technical design, development, testing, and delivery of solutions Document business requirements and specifications for reporting requests Manage assigned projects and support activities of team Ensure prompt completion and accuracy of assigned projects Identify and evaluate recurring data issues and implements solutions Serve as reporting expert for the team by developing report requests and interpreting data Provide guidance, training, and problem-solving assistance to other team members Perform other duties as assigned   Position Requirements: 1 years of SQL or SAS experience Bachelor’s Degree required; preferred majors include: Business, Mathematics, Statistics, Engineering, or Computer Science 1 years work experience in a similar role in a professional corporate environment Experience data mining large databases Preferred: Advanced degree in Business, Mathematics, or Computer Science Consumer Credit Card industry experience 5 years advanced use of at least one of the following: SQL Server, Oracle, or SAS Experience with web analytics Statistical modeling exposure including logistic regression, CHAID/CART analysis, and other general linear models

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