Summary: This individual contributor role will support consumer risk scoring related modeling, documentation, and adhoc analytics for International and US consumer portfolios including credit cards, loans, and others at Citi by using traditional (e.g., regression) as well as emerging (e.g., machine learning and artificial intelligence ) predictive modeling techniques. Role requires hands-on experience in Python, SAS, SQL to perform data processing, predictive modeling, and development of library of automated scripts such as Python functions and SAS macros. Role provides broad exposure to business teams, other risk modeling teams, and model risk management group which requires strong communication, presentation, and stakeholder management.

Responsibilities

• Pull, prepare, process required data from various databases in Big Data and Unix environments using tools such as SQL, Hive, Hue and derive insightful predictors
• Perform model development steps including project design, segmentation, model fitting, alternative model development using SAS, Python, and PySpark
• Perform model diagnostics, performance testing, benchmarking to complete model documentation according to best practices and internal guidelines
• Use strong understanding of the financial service Industry, consumer lending and associated regulatory framework such as Fair lending, model risk management
• Structurally articulate technical information in writing and verbally to both technical and non-technical stakeholders

Qualifications

• 5-8 years experience with at least 1 years hands-on experience in predictive modeling preferably in consumer lending
• Working knowledge of Python (pandas, numpy, sklearn), SAS, SQL especially in data processing and predictive modeling such as regression, machine learning (random forest, GBM, neural nets)
• Preferred knowledge of big data tools such as PySpark, Hadoop, Hive etc
• Preferred knowledge of at least one of the following: scoring model development, PD, EAD, LGD, Basel, CCAR, CCEL modeling

Education

Bachelor’s/University degree or equivalent experience, potentially Masters degree

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