Global Credit Risk Data Scientist
CNH Industrial (company site, opens in a new tab)2+ yrsGurugramOn-siteDirect career pageEst. 12–20 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop, refine, and implement credit risk models using machine learning and statistical techniques for retail and commercial lending across multiple global regions.
- Manage, prepare, and analyze large datasets to support risk-centric projects and enhance predictive model performance.
- Collaborate with IT and risk teams to maintain data structures, validate models, monitor risk tools, and present data analysis to management and audit reviews.
Minimum Requirements
- Minimum 2 years of experience in advanced algorithms and statistical models including machine learning, logistic regression, hazard rate, time series, or simulation.
- Strong programming skills in Python, SAS, R, or similar languages and experience with Big Data technologies.
- Bachelor’s degree or MBA in Analytics, Data Science, Statistics, Mathematics, Economics, Finance, Engineering or related quantitative discipline.
- Work Experience Required: Minimum 2 years in relevant modeling and data science roles.
Ideal Candidate Profile
- Experience working in global or multinational financial services or industrial credit risk environments, especially with retail and commercial lending models.
- Strong analytical orientation with ability to operate independently and manage multiple projects in a fast-paced environment.
- Proven ability to collaborate cross-functionally with IT, external data vendors, and risk stakeholders to improve and maintain modeling infrastructure.