Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
5+ years professional experience developing credit risk models
Strong Programming skills e.g. R, Python, SAS, SQL or other languages
Strong analytical and problem-solving skills
Experience using and developing cross-sectional models
Experience implementing models into various production environments
Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data
Effectively presents findings, data, and conclusions to influence senior leaders
Demonstrated leadership skills; Ability to exert broad influence among peers
Ability to work in a large, complex organization, and influence various stakeholders and partners
Self-starter; Initiates work independently, before being asked
Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Effective at prioritization, and time and project management
Sees the broader picture and is able to identify new methods for doing things
Strategic thinker that can understand complex business challenges and potential solutions
Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
Experience developing and maintaining complex databases and data sets
Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting
Experience managing large data sets utilizing tools such as Hadoop
Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
Experience with data analytics and visualization tools (e.g., Alteryx, Tableau, MicroStrategy)
Experience with LaTeX
Experience building data architecture that is optimized for large dataset retrieval, analysis, storage, cleansing, and transformation
Demonstrated ability to drive action and sustain momentum to achieve results
Identifies, assigns, and manages project tasks and timelines across teams
Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow.