Data Scientist (Credit Risk)
Analyze & interpret data and communicate results to clients, often with the aid of mathematical/statistical techniques and software.
- This role requires building Credit Risk, Fraud, Bad Debt, Write off, Collection Scorecard.
- Data exploration, mathematical/statistical modeling, data analysis, and hypothesis testing.
- Design, development, and deployment of Predictive models and frameworks.
- Complex statistical concepts are explained in a way that clients can understand and advice on strategy.
Requirements and General Skills
- 1-3 years of overall experience in R, Python, and in Different Model Development.
- Must have experience in the building following scorecard:
- Credit risk
- Bad Debt
- Write Off
- Knowledge of different libraries in R and Python and their implementation.
- Strong Analytical and problem-solving skills.
- Knowledge of different Machine Learning models and their implementation.
- Strong database experience in SQL and My SQL.
- Knowledge in data processing and analysis.
- Organizational and time management skills required.
- Well-versed in quantitative analysis, research, data mining, trend analysis, customer profiling, clustering, segmentation, and predictive modeling.
- Executing the data-driven planning process by building models and frameworks that connect business unit drivers to company financials and forecast to take the correct decision as per the business need.
- Design and build dashboards and other visualizations in BI tools.
- Should be able to handle assigned tasks in the capacity of an individual contributor.
- Hands-on experience in R and Python.
- Good understanding and experience in the implementation of different packages of R and Python.
- Proficiency in SQL and MySQL.
- Proficient understanding of different analytical and database tools and their implementation.
- Knowledge of Neural Networks.
To apply, send your cv at email@example.com