Job Description Credit Risk Data Analyst –SQL, Python & PySpark N Experience: 3–7 Years N Location: Bangalore N Notice - Immediate to 15 Days N Role Summary NSeeking 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 effective processing within modern data platforms. N Key Responsibilities Nn Perform large-scale data processing, transformation, and validation using Python and PySpark N Build and optimize datapipelines for ingestion, processing, and analysis of credit risk datasets N Conduct exploratory data analysis (EDA), anomaly detection, and trend identification N Implement data quality checks covering accuracy, completeness, and consistency N Perform data reconciliation and support data migration validation activities N Work with distributed data environments (e.G., big data platforms)
to handle high-volume datasets N Collaborate with stakeholders to understand business requirements and data flows N Assist in preparing andvalidating datasets used in PD, LGD, and EAD models N Partner with data engineering and risk teams to improve data processing efficiency Nn Required Skills Nn Strong hands-on experience in Python and PySpark N Experience in building and optimizing data pipelines in distributed environments N Solid understanding of data transformation, validation, and big data processing N Exposure to data quality frameworks and governance practices Nn Domain Requirements (Uniform Across JDs) Nn Robust understanding of Credit Risk fundamentals N Exposure to PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) models N Knowledge of retail banking portfolios such as loans, cards, and mortgages N