CNH AMERICA LLC Data Scientist - Credit Risk Analytics in RACINE, Wisconsin
JOB REQUIREMENTS: Overview 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, N ew Holland Agriculture, Case and New Holland Construction, FPT Industrial, Capital, and Aftermarket Solutions, is a major international force in its specific sector. The Data Scientist - Credit Risk Analytics 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 hand le multiple projects simultaneously. Responsibilities * Apply Machine Learning (ML) techniques on big data to d evelop, 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, p erform 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 h igh quality fashion and acceptable format, for management, peer and audit reviews * Document and maintain all procedures and models steps Qualifications * Bachelor degree in a quantitative discipline or related fields (e.g. Analytics, Data Science, Statistics, Mathematics, Economics, Finance, Engineering, etc.) * 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.) Preferred: * MBA * Strong programming knowledge (R, Python, SAS, and others) * Strong knowledge and experience in Big Data * Strong interpersonal, written and verbal communication skills * Previous Credit risk and/or financial services experience * SAS * MBA in a quantitative discipline or related fields * Problem solving skills and ability to propose and implement creative solutions * Ability to work both independently a nd as part of a team * Analytically-oriented with a strong logical and quantitative skills * Familiarity with credit bureaus and alternative credit data sources EEO US applicants: CNH Industrial is an equal opportunity employer. This company considers candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Applicants can learn more about their rights by viewing the federal "EEO is the Law" poster and its supplement here. CNH Industrial participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are autho To view the full job description please use the link below. https://www.aplitrak.com/?adid=YmJnZW5lcmljLjQ1MTYzLjg3NzBAY25oaW5kY29tcC5hcGxpdHJhay5jb20 ***** APPLICATION INSTRUCTIONS: Apply Online: https://www.aplitrak.com/?adi =YmJnZW5lcmljLjQ1MTYzLjg3NzBAY25oaW5kY29tcC5hcGxpdHJhay5jb20 Qualified females, minorities, and special disabled veterans and other veterans are encouraged to apply.