Credit Risk Analytics & Strategy

  • New York, NY
  • Posted 4 hours ago | Updated 4 hours ago

Overview

Hybrid
Up to $120,000
Full Time

Skills

Data Analyst
Credit risk
SQL
Python
Credit Card
Banking

Job Details

Key Responsibilities:

Credit Risk Monitoring: Continuously monitor risk exposures, identify and escalate potential credit risk issues to senior management and the risk committee to ensure timely mitigation.
Credit Risk Strategy Development: Develop, maintain, update & implement credit risk policies, procedures, and guidelines to ensure alignment with regulatory requirements and industry best practices.

Credit Risk Modelling: Develop, maintain, and validate credit risk models to estimate potential losses and predict credit risk. Collaborate with data scientists and analysts to integrate credit risk models with other risk models.

Stakeholder Management: Inform and advise senior management, business units, and stakeholders on credit risk, and provide training on credit risk management and policies.

Data Analysis and Reporting: Analyze large datasets to identify credit risk trends, and present findings to senior management using SQL, Python, and data-driven insights, providing clear and compelling recommendations.
Credit Risk Assessment: Analyze and evaluate creditworthiness of customers, counterparties, and transactions to identify potential credit risks. Conduct thorough credit reviews, including financial statement analysis, industry research, and market trends.

Regulatory Compliance: Ensure compliance with credit risk regulations, such as Basel II/III, Dodd-Frank, and other applicable laws and regulations. Collaborate with regulatory teams to respond to regulatory inquiries and examinations.

Qualifications:
Bachelor s degree in finance, Economics, Data Science, Engineering or a related field; master s degree preferred.
Minimum of 3-4 years of experience in credit card analytics, with a focus in at least one of the following areas - Credit risk/Collection/Recoveries Analytics
Proficient in SQL and Python; experience with data visualization tools (e.g., Tableau, Power BI) is a plus.
Excellent analytical and problem-solving skills, with the ability to interpret complex data and make informed decisions.
Strong communication and presentation skills, with the ability to convey technical information to non-technical stakeholders.

Proven ability to work collaboratively in a fast-paced, team-oriented environment.

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