2+ years of experience in financial services or data analytics.
Proficient in AI-assisted coding tools and platforms.
Strong SQL skills across various databases (MS SQL Server, Sybase, Oracle).
Knowledge of Python and/or R with a focus on statistical and machine-learning techniques.
Familiarity with DevOps tools like Git and Jira.
Excellent communication skills for conveying complex data insights to non-technical audiences.
Understanding of credit and market risk concepts.
Responsibilities
Partner with Risk Management to gather and document analytics requirements.
Build and enhance risk processes through data analysis and asset valuation.
Design and deliver user-friendly dashboards for diverse audiences.
Write clear documentation for stakeholders, regulators, and auditors.
Implement industry-standard practices for source control and deployment.
Utilize AI-assisted coding tools to improve development efficiency.
Evaluate and recommend emerging technologies for integration into risk applications.
Benefits
Broad exposure to various asset classes and risk methodologies.
Hands-on role with the full data lifecycle from source systems to dashboards.
Opportunity to work closely with front-office and technology teams.
Engagement with cutting-edge technologies in risk analytics.
Full Job Description
Job Description
The Data Analyst will work side-by-side with Risk Management to translate business requirements into reliable, well-documented analytics that drive real-world decisions. This hands-on role offers broad exposure across asset classes, risk methodologies, and the full data lifecycle-from source systems to the dashboards risk managers rely on-while evaluating and integrating emerging technologies.
Responsibilities
Partner with Risk Management to gather, refine, and document requirements.
Build and enhance risk processes, including data analysis, asset valuation, and custom risk measure calculations.
Design and deliver dashboards and visualizations for technical and non-technical audiences.
Write clear documentation for internal stakeholders, regulators, and auditors.
Follow industry-standard source control, code review, testing, and deployment practices.
Leverage AI-assisted coding tools to accelerate development while ensuring accuracy.
Evaluate emerging technologies and recommend integration into Risk Technology applications.
Develop and maintain ETL pipelines and data models supporting risk analytics.
Ensure data quality and integrity across source systems to dashboards.
Collaborate with front-office and technology teams to implement risk solutions.
Qualifications
2+ years of professional experience in financial services or data analytics.
Proficiency with AI-assisted coding tools and platforms.
