Key Responsibilities:
- Develop and maintain Acquisition Scorecards using Advance Machine Learning Algorithms and identify new opportunities.
- Hands-on experience on various programming languages, such as Python, SQL and tools like Excel, exposure of banking data (preferred).
- Hand-on experience on various machine-learning techniques like Logistic Regression, Random Forest, Decision Tree, XGBoost etc.
- Identify alternate data sources for improvisation of existing models.
- Analyze and interpret large datasets to draw conclusions and identify trends.
- Proactive Risk Management through Early Warning Models using Internal and External data
- Design innovative Analytical Solutions for Proactive Risk Management
- Process and Operational Risk Management
- Portfolio Analytics and Segmentation for Policy Reviews
- Collaborate with Business Teams to identify the problem and with Tech Team for solution deployment
- Design Dashboards for Performance Monitoring
- Collaborate with Vendors and Fin-Tech Partners to identify applicable solutions for Process Digitalization & Improvisation Competencies
Candidate attributes:
1. Knowledge and experience of the Python Data Analysis stack (pandas, numpy, sklearn) (advanced); building ML pipelines and scorecards
2. Must have experience in Finance/NBFC sector.
3. Understanding of Regular Expressions (advanced).
4. 2-4 years coding experience in Python.
5. Fluent in data analysis in MS Excel
