Credit Risk Analyst - Data & Modeling, Bonus Eligible

Socket.dev; New York (NY); On-site; USD 75,991,000 - 104,485,000; Full time

Job summary

Socket.dev seeks a Credit Risk Analyst to support the Credit Management Division with loan and data analytics, risk assessment, and stress testing. You will work on COSO and SOX controls, enhance the loan accounting system, and contribute to data-related projects.

You will collaborate with Credit Risk Officers and IT, develop and document models, and automate reporting processes to improve efficiency across departments.

Qualifications

• Bachelor's degree (B.A.) from four-year college or university; or one to two years related experience.
• Ability to query and manipulate data using SQL or similar tools to support reporting and analysis.
• Experience with credit risk models such as Moody’s CMM, RiskCalc, and Challenger Models.

Responsibilities

• Prepare and deliver analyses for internal and external stakeholders using data extracts. Summarize large datasets and produce reports under deadlines.
• Develop and maintain models to assess loan portfolio and perform stress testing.
• Support regulatory examinations and internal audits by interfacing with examiners and auditors.
• Identify opportunities to improve internal processes and automate reports to drive efficiency.
• Serve as a subject matter expert on loan source system data and educate team members on data usage and standards.
• Collaborate across Credit, IT, and Compliance during system or program implementations.

Skills

Excel

Access

R

Python

VBA

Analytical mindset

Education

Bachelor's degree

Tools

Moody’s CMM

RiskCalc

Challenger Models

Job description

Socket.dev seeks a Credit Risk Analyst to support the Credit Management Division with loan and data analytics, risk assessment, and stress testing. You will work on COSO and SOX controls, enhance the loan accounting system, and contribute to data-related projects.

You will collaborate with Credit Risk Officers and IT, develop and document models, and automate reporting processes to improve efficiency across departments.