Credit Risk Data Analyst

Location: Bengaluru

Credit Risk Data Analyst –SQL, Python & Py Spark

Experience:

3–7 Years

Location:

Bangalore
Notice - Immediate to 15 Days

Role Summary
Seeking a Credit Risk Data Analyst with strong hands-on expertise in  Python and PySpark  to support large-scale data processing, validation, and analytics across credit risk datasets. The role focuses on leveraging distributed data frameworks to ensure data accuracy, scalability, and efficient processing within modern data platforms.

Key Responsibilities
Perform large-scale data processing, transformation, and validation using Python and Py Spark
Build and optimize data pipelines for ingestion, processing, and analysis of credit risk datasets
Conduct exploratory data analysis (EDA), anomaly detection, and trend identification
Implement data quality checks covering accuracy, completeness, and consistency
Perform data reconciliation and support data migration validation activities
Work with distributed data environments (e.g., big data platforms) to handle high-volume datasets
Collaborate with stakeholders to understand business requirements and data flows
Assist in preparing and validating datasets used in PD, LGD, and EAD models
Partner with data engineering and risk teams to improve data processing efficiency

Required Skills
Strong hands-on experience in  Python and Py Spark
Experience in building and optimizing data pipelines in distributed environments
Solid understanding of data transformation, validation, and big data processing
Exposure to data quality frameworks and governance practices

Domain Requirements (Uniform Across JDs)
Strong understanding of  Credit Risk fundamentals
Exposure to  PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default)  models
Knowledge of retail banking portfolios such as loans, cards, and mortgages