Credit Risk Data Analyst - Client & Markets (Hybrid)

Citi; New York (NY); Hybrid; USD 87,000 - 131,000; Full time

Job summary

Citi is seeking a Data Analyst for Credit Risk Management & Counterparty Risk (Client & Markets Data) in a hybrid role based in the United States. The role focuses on examining credit risk, liquidity, and reference data, with collaboration across technology teams to remediate data issues and to support risk reporting.

The ideal candidate has 4–5 years of data analytics experience in financial markets, strong SQL/Python skills, and hands-on use of Excel and Tableau to produce actionable insights

Qualifications

• 4-5 years' experience performing data analytics with financial markets data and products.
• At least 1 year of experience in SQL or Python scripting.
• Hands-on Experience leveraging tools such as Excel, Tableau, SQL and Python to perform data analysis.
• Understanding of how firms manage Credit and Market Risk for trading book activity.

Responsibilities

• Analyzes Credit Risk Management, Liquidity Management, and related data sets.
• Gathers operational data from various cross-functional stakeholders.
• Identifies data patterns and trends.
• Provides insights to enhance business decision-making in areas such as business planning, process improvement, and solution assessment.
• Discusses data issues with technology teams to design and deliver remediation solutions.
• Discusses data requirements and the impact of data issues with data consumers, as raised in the DCRM tool.

Skills

Data analytics

SQL

Python

Excel

Tableau

Communication

Education

Bachelor's degree in Computer Science or equivalent

Master's degree preferred

Tools

SQL

Python

Excel

Tableau

Job description

Citi is seeking a Data Analyst for Credit Risk Management & Counterparty Risk (Client & Markets Data) in a hybrid role based in the United States. The role focuses on examining credit risk, liquidity, and reference data, with collaboration across technology teams to remediate data issues and to support risk reporting.

The ideal candidate has 4–5 years of data analytics experience in financial markets, strong SQL/Python skills, and hands-on use of Excel and Tableau to produce actionable insights