Job Description

The Risk Technology Data Analyst will be a key member of the Risk Management Technology team, contributing to the development and enhancement of risk systems. This role offers an opportunity to work with a dynamic team, utilizing cutting-edge technologies to manage and mitigate risks across the enterprise.

Responsibilities

• Collaborate with Risk Management to gather and analyze requirements for risk systems.
• Build and enhance data analysis processes, including asset valuations and custom measure calculations.
• Present data using visualization tools, creating clear and concise reports.
• Create documentation for internal and external stakeholders, ensuring compliance with regulatory standards.
• Implement industry-standard practices for source control and application deployment.
• Evaluate new technologies for their applicability to Risk Technology applications.
• Work on integrating risk systems with trading, middle office, and clearing systems.
• Manage security and client reference data, ensuring data integrity and accuracy.
• Build management dashboards and reports, providing insights for decision-making.
• Stay updated with industry trends and best practices in risk management and technology.

Qualifications

• Proficiency with AI Coding Tools and Platforms is a must, along with strong SQL skills and database management experience (MS SQL Server, Sybase, Oracle).
• Excellent programming skills in Python and R, with a deep understanding of statistical and machine learning concepts.
• Experience with DevOps Solutions, particularly Git and Jira, is essential.
• Desirable skills include experience with Credit and Market Risk, MCSI/Risk Metrics, and ETL tools like Pentaho/Hitachi Vantara.
• Knowledge of Risk Management, Margin, and Fund Accounting systems (Imagine, Seamans) is an advantage.
• Familiarity with Markup/Markup Schemas (JSON, xml) and RESTful services is preferred.
• A strong analytical mindset and the ability to work with complex datasets are key.
• Excellent communication skills for effective collaboration with Risk Management.
• A proactive and self-motivated approach to work, with a focus on continuous improvement.
• A relevant degree in Computer Science, Mathematics, Statistics, or a related field is preferred.