CNH Industrial is looking to solve credit, collections, and residual value risk within their agricultural and construction equipment business by analyzing diverse data sets and applying machine learning algorithms.
Requirements
- Bachelors or Master's degree in a quantitative discipline or related fields (e.g. Analytics, Data Science, Statistics, Mathematics, Economics, Finance, Engineering, Computer Science etc.)
- Prior experience in data querying dashboard development
- Prior experience working in Python/SAS and/or Azure Databricks
- Experience in delivering information to business stakeholders through quantitative methodologies
Responsibilities
- Develop and implement AI/ML models for the credit, collections, and residual risk
- Provide data-driven solutions to stakeholders within the business by using various digital tools available within CNH Capital
- Perform ad hoc analyses of business situations, systems, issues and problems as well as research and test new technologies for risk mitigation
- Work with IT to create/improve and keep structured data, perform data maintenance and management, and consult on best practices for data retention
- Assess tools/data purchased to support risk management plus tools used by outside vendors or partners
- Provide and present the results of analyses in the form of graphs, charts, and tables, in high quality fashion and acceptable format, for management, peer and audit reviews
- Validation and monitoring of Residual Value tools and their application in sales, underwriting, remarketing or other user areas
Other
- Bachelors or Master's degree in a quantitative discipline or related fields
- This position is not eligible for visa sponsorship
- Candidates must have current authorization to work in the United States without the need for future sponsorship
- Flexible work arrangements
- Savings & Retirement benefits
