Job Details

Job Title	Credit Risk Data Scientist
Posted On	14-05-2025
Experience	8
Job Location	Remote
No. of Positions	1

Details :-

Job Title: Credit Risk Data Scientist

Location: Remote
Department: Risk Management / Data Science

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Job Summary:

We are seeking a highly analytical and detail-oriented Credit Risk Data Scientist to join our Risk Analytics team. In this role, you will be responsible for developing and deploying statistical and machine learning models to assess and manage credit risk across our portfolio. Your work will directly influence lending decisions, risk strategies, and overall business performance.

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Key Responsibilities:

• Develop, validate, and monitor credit risk models (e.g., PD, LGD, EAD) using statistical and machine learning techniques.

• Analyze large datasets to identify patterns, trends, and risk indicators.

• Support the design and implementation of risk scoring models for underwriting, collections, and portfolio monitoring.

• Work closely with cross-functional teams (Credit, Product, Finance, Compliance) to align risk models with business objectives.

• Use tools like Python, R, SQL, SAS, and Spark for data analysis and model development.

• Perform model validation, backtesting, and sensitivity analysis to ensure robustness and regulatory compliance.

• Prepare detailed documentation for models to meet internal governance and regulatory standards (e.g., SR 11-7, Basel, IFRS 9, CCAR).

• Monitor performance of deployed models and recommend enhancements as needed.

• Communicate complex analytical concepts and risk metrics to both technical and non-technical stakeholders.

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Qualifications:

Required:

• Master’s or PhD in Statistics, Data Science, Economics, Finance, Mathematics, or related field.

• 8+ years of experience in credit risk modeling or analytics.

• Proficiency in Python, R, SQL, and statistical modeling tools.

• Experience with machine learning algorithms and large-scale data processing.

• Strong understanding of credit lifecycle, risk metrics, and financial products (e.g., personal loans, credit cards, mortgages).

Preferred:

• Experience with regulatory requirements such as Basel II/III, IFRS 9, CCAR, SR 11-7.

• Background in consumer or commercial lending.

• Experience with cloud platforms (AWS, GCP, Azure) and big data tools like Hadoop or Spark.

• Knowledge of BI tools (e.g., Tableau, Power BI) for dashboarding and visualization.

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Soft Skills:

• Strong analytical thinking and problem-solving skills.

• Ability to communicate insights clearly to non-technical stakeholders.

• Detail-oriented with a high standard of data integrity and accuracy.

• Comfortable working in a fast-paced, agile environment.