Data Scientist – Credit Risk Modelling

Experience: 7+ Years

Location: Mumbai – Work from Office

Notice Period: Immediate to 30 Days

Job Overview

We are seeking an experienced Data Scientist – Credit Risk Modelling with strong expertise in predictive analytics, statistical modelling, and credit risk analytics. The ideal candidate will have a proven track record of developing and implementing credit risk models and scorecards within the Banking or Financial Services domain.

The role will involve working closely with risk, business, and technology teams to develop data-driven analytical solutions, enhance model performance, and support model validation, governance, and regulatory requirements.

Key Responsibilities

- Develop, implement, and enhance Credit Risk Models for retail and corporate lending portfolios.
- Design, build, validate, and monitor predictive models for credit risk assessment.
- Develop and maintain Application, Behavioral, and Collection Scorecards.
- Perform statistical analysis to identify key risk drivers and improve model accuracy and performance.
- Analyze large and complex datasets to derive actionable business and risk insights.
- Conduct model validation, monitoring, recalibration, and performance assessment.
- Ensure risk models align with applicable regulatory, governance, and compliance requirements.
- Collaborate with business stakeholders, risk teams, and technology teams to translate business requirements into analytical solutions.
- Prepare comprehensive model documentation, analytical reports, presentations, and regulatory submissions.
- Support model governance, independent validation, audit, and regulatory review activities.
- Contribute to continuous improvement of risk analytics methodologies, modelling frameworks, and processes.

Mandatory Skills & Experience

Core Experience





- 7+ years of experience as a Data Scientist, Credit Risk Analyst, Risk Modelling Analyst, or similar role.
- Strong hands-on experience in Credit Risk Modelling.
- Proven experience in Predictive Modelling and statistical analysis.
- Hands-on experience in Scorecard Development.
- Strong understanding of statistical modelling techniques and risk analytics.
- Relevant experience within the Banking, NBFC, or Financial Services domain.

Technical Skills
- Credit Risk Modelling
- Predictive Modelling
- Statistical Modelling
- Application, Behavioral & Collection Scorecards
- Data Analysis & Data Mining
- Python / R / SAS
- SQL
- Machine Learning Algorithms
- Advanced Excel
- Data Visualization using Power BI / Tableau – Preferred

Preferred Skills
- Working knowledge of Basel regulations and IFRS 9 modelling.
- Understanding of Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models.
- Experience developing risk models using SAS, Python, or R.
- Experience in Model Validation, Model Monitoring, and Model Governance.
- Strong understanding of risk analytics, regulatory reporting, and model lifecycle management.
- Experience working with large-scale financial and credit datasets.

Soft Skills
- Strong analytical and problem-solving capabilities.
- Excellent communication and stakeholder management skills.
- Ability to work independently as well as collaboratively in a fast-paced workplace.
- Strong attention to detail and commitment to data quality and accuracy.
- Ability to effectively communicate complex analytical and modelling concepts to both technical and non-technical stakeholders.

Educational Qualification Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or another relevant quantitative discipline.

📌 Data Scientist – Credit Risk Modelling (7+ Years ) (Bengaluru)
🏢 MindBrain
📍 Bengaluru