Job Description

Credit Risk Data Analyst –SQL, Python & PySpark

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Experience: 3–7 Years

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Location: Bangalore

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Notice - Immediate to 15 Days

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Role Summary

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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.

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Key Responsibilities

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- Perform large-scale data processing, transformation, and validation using Python and PySpark
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- Build and optimize data pipelines for ingestion, processing, and analysis of credit risk datasets
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- Conduct exploratory data analysis (EDA), anomaly detection, and trend identification
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- Implement data quality checks covering accuracy, completeness, and consistency
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- Perform data reconciliation and support data migration validation activities
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- Work with distributed data environments (e.g., big data platforms)



to handle high-volume datasets
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- Collaborate with stakeholders to understand business requirements and data flows
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- Assist in preparing and validating datasets used in PD, LGD, and EAD models
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- Partner with data engineering and risk teams to improve data processing efficiency
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Required Skills

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- Robust hands-on experience in Python and PySpark
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- Experience in building and optimizing data pipelines in distributed environments
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- Solid understanding of data transformation, validation, and big data processing
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- Exposure to data quality frameworks and governance practices
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Domain Requirements (Uniform Across JDs)

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- Strong understanding of Credit Risk fundamentals
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- Exposure to PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) models
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- Knowledge of retail banking portfolios such as loans, cards, and mortgages
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📌 Credit Risk Data Analyst (Bengaluru Urban)
🏢 Etenico Technologies
📍 Bengaluru Urban