VP- Risk Data Scientist- C13

Key Skills

3D data processing, Apache Hive, Big Data Technology, Data science techniques, Database, Design, Effective communication skills, NumPy, Pandas, PySpark, Python Programming, Random forests, SAS, SQL

Job Description

The Model/Anlys/Valid Officer is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.

Summary: This role will support consumer risk scoring related team supervision, modeling, documentation, and adhoc analytics for International and US consumer portfolios including credit cards, loans, mortgages, 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 requires strong familiarity and experience in model risk management related documentation, guidelines, and related analyses. 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

• 10-12 years experience with at least 4 years hands-on experience in predictive modeling preferably in consumer lending and 2 years of management experience
• 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

Education

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