Job DescriptionCredit Risk Data Analyst –SQL, Python & PySpark
nExperience: 3–7 Years
nLocation: Bangalore
nNotice - Immediate to 15 Days
nRole Summary
nSeeking a Credit Risk Data Analyst with solid 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 contemporary data platforms.
nKey Responsibilities
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Perform large-scale data processing, transformation, and validation using Python and PySparkn
Build and optimize data pipelines for ingestion, processing, and analysis of credit risk datasetsn
Conduct exploratory data analysis (EDA), anomaly detection, and trend identificationn
Implement data quality checks covering accuracy, completeness, and consistencyn
Perform data reconciliation and support data migration validation activitiesn
Work with distributed data environments (e.g., big data platforms)
to handle high-volume datasetsn
Collaborate with stakeholders to understand business requirements and data flowsn
Assist in preparing and validating datasets used in PD, LGD, and EAD modelsn
Partner with data engineering and risk teams to improve data processing efficiencyn
nRequired Skills
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Strong hands-on experience in Python and PySparkn
Experience in building and optimizing data pipelines in distributed environmentsn
Solid understanding of data transformation, validation, and big data processingn
Exposure to data quality frameworks and governance practicesn
nDomain Requirements (Uniform Across JDs)
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Strong understanding of Credit Risk fundamentalsn
Exposure to PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) modelsn
Knowledge of retail banking portfolios such as loans, cards, and mortgagesn