Data Science Analyst

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

As Credit Risk Data Scientist, you will join our Global Risk team in CNH Industrial Financial Services. Being member of a global team, you should expect being involved with projects of other regions, supporting data science standards, ad hoc and periodical risk-centric projects with focus on preparing, managing, and analyzing multiple data sets, applying machine learning algorithms to build credit risk models, as well as following established policies and procedures for developing and distributing standard reports. Also, you are encouraged to collaborate with other risk team members and stakeholders from across the organization to initiate and implement creative business solutions which meet business needs. To be successful in this role, you 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 balance multiple projects simultaneously.

This position follows a HYBRID work model from our Racine, WI office

The annual salary range is $85,000.00 - $115,000.00 plus potential for a lump sum annual bonus (Actual salaries will vary and will be based on various factors, such as skill, experience and qualification for the role.)

Responsibilities

• 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, delinquency, fraud, losses and auto-approval
• Work with IT to build/improve and keep structured data, perform data maintenance and management on daily basis, and consult on standard processes for data retention
• Work to strengthen/increase partnership with external data suppliers worldwide, growing 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
• Validation and monitoring of risk tools and their application in underwriting, collection or other user areas

Qualifications

• Bachelors degree in a quantitative subject area or related field (e.g. Analytics, Data Science, Statistics, Mathematics, Economics, Finance, Engineering, etc.)
• 2+ years of experience creating/applying sophisticated algorithms and/or statistical models such as (machine learning techniques, Logistic regression, hazard rate, time series, Simulation, etc.)