Credit Risk Model Development Intmd Analyst

This position is with Global Consumer Bank (GCB) Risk Modeling Utility. This specific role supports the US Consumer Banks Branded Cards portfolios. Citi-branded card products include its proprietary portfolio (including the Citi Double Cash, Thank You and Value cards) and co-branded cards (including, among others, American Airlines and Costco). In this role, you will build Account Management Risk Models using traditional and Machine Learning techniques. You will develop these models in compliance with the Risk modeling policies and procedures. Leveraging a variety of technologies such as SAS, R, Python, H2O, Spark, and more to extract the value out of the data. Deliver on all phases of development, from design through training, testing, validation, and implementation. Work with Technology, Risk policy and Governance teams to deliver decision risk models in the market. Practice your presentation and articulation skills to translate the complexity of your work to all types of audience. We will be thrilled to have someone who is curious, challenges the status quo, questions what they see, and looks for answers when something is not intuitive. Has attention to details, knows when something does not add up and is not right. Has the ability to communicate results to diverse audiences. Qualifications: - 4+ years experience in Risk Modeling or a PhD degree in statistics, economics, or equivalent experience. - Sound knowledge of statistical modeling concepts and industry best practices; experience with econometric and statistical modeling or risk models. - Excellent quantitative and analytic skills; ability to derive patterns, trends, and insights. - Experience with analytical or data manipulation tools (e.g. SAS, SQL, R, Python, Spark) Proficient with MS Office suite. - Consistently demonstrates clear and concise written and verbal communication skills. - Self-motivated and detail-oriented. - Experience working in big data environments; Intellectual curiosity to stay abreast of technological advances. Education: - Bachelors/University degree in statistics, mathematics, economics, or equivalent experience. Masters/PhD degree is a plus.,