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.
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