Cantor Fitzgerald
Risk Technology Data Analyst
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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.
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Qualifications
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- 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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