Data Scientist (Credit Risk)

Position Summary

Analyze & interpret data and communicate results to clients, often with the aid of mathematical/statistical techniques and software.

  1. This role requires building Credit Risk, Fraud, Bad Debt, Write off, Collection Scorecard.
  2. Data exploration, mathematical/statistical modeling, data analysis, and hypothesis testing.
  3. Design, development, and deployment of Predictive models and frameworks.
  4. 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
    • Fraud
    • Bad Debt
    • Write Off
    • Collection
  • 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.


Technical Skills
  • 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.





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