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Through its people and brands, CNH Industrial delivers power, technology and innovation to farmers, builders and drivers all around the world. Each of its brands, including Case IH, New Holland Agriculture, Case and New Holland Construction, FPT Industrial, Capital, and Aftermarket Solutions, is a major international force in its specific sector.
The Credit Risk Analytics-Data Scientist Manager will join our Risk team in Racine, WI. In this position, you are expected to support the team’s standard, ad hoc and periodical risk-centric projects with focus on preparing, managing, and analyzing multiple data sets, applying machine learning algorithms to create risk models, as well as following established policies and procedures for developing and distributing standard reports. Also, you are expected to collaborate with team members and other stakeholders from across the organization to initiate and implement creative business solutions which meet business needs. To be successful in this role, the Manager must have very strong quantitative, logical, analytical and problem-solving skills, being able to work with little supervision in a fast‐paced environment, and to handle multiple projects simultaneously.
Apply Machine Learning (ML) techniques on big data to develop, refine and implement retail/commercial lending models as well as associated alignments and cutoffs for all regions. Models included but not limited to: origination, behavior, collection, financial, bureaus, depreciation curve, delinquency, fraud, etc.
Work with IT to create/improve and keep structured data, perform data maintenance and management on daily basis
Work to strengthen/increase partnership with external data suppliers worldwide, expanding our options to improve our models prediction power
Assess tools/data purchased to support risk management plus tools used by outside vendors or partners
Perform ad hoc analyses of business situations, systems, issues and problems as well as research and test new technologies for risk mitigation
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
Document and maintain all procedures and models steps
The qualified candidate will have:
Bachelor degree in a quantitative discipline or related fields (e.g. Analytics, Data Science, Statistics, Mathematics, Economics, Finance, Engineering, etc.)
Minimum of 3 years of experience creating/applying advanced algorithms and/or statistical models such as (machine learning techniques, Logistic regression, hazard rate, time series, Simulation, etc.)
Strong programming knowledge (R, Python, SAS, and others)
Strong knowledge and experience in Big Data
Strong interpersonal, written and verbal communication skills