Algorithm Specialist

Role                           : Algo System SME|| Location          : Dublin, IRE||Hybrid                               : 2 Days/week to Dublin.

Duration: 6 Months|| SME - Algo tool for Credit Risk & Real-Time global limits management for Banking.

Overview:

The job is focused on developing, maintaining, and optimizing an algorithmic tool designed for banking institutions to manage credit risk efficiently. The tool must operate in real-time and be capable of handling global limits that impact credit decisions.

Responsibilities:

1. Algorithm Development and Optimization:
2. Design and implement robust algorithms that assess credit risk dynamically.
3. Optimize algorithms for real-time processing and decision-making.
4. Continuously monitor and refine algorithms to enhance accuracy and performance.
5. Credit Risk Analysis:
6. Gather and analyze data to identify potential credit risks.
7. Use statistical and machine learning methods to predict risk factors.
8. Implement models that integrate both macro and microeconomic indicators affecting credit risk.
9. Global Limits Management:
10. Design systems to monitor and enforce global credit limits across various jurisdictions.
11. Implement alerts and safeguards to prevent breaches of credit limits.
12. Cross-functional Collaboration:
13. Work closely with data scientists, credit analysts, and IT teams to integrate risk models with existing banking frameworks.
14. Collaborate with regulatory compliance teams to ensure adherence to legal and financial regulations worldwide.
15. Real-time Data Processing:
16. Develop infrastructure capable of ingesting and processing large volumes of data in real-time.
17. Utilize cloud computing and distributed systems to maintain tool performance and scalability.
18. User Interface and Reporting:
19. Create intuitive interfaces for end-users to interact with the tool.
20. Develop comprehensive reporting mechanisms to convey risk assessments and limit statuses.

Qualifications:

• Proven experience in financial engineering, data science, or risk management fields.
• Strong knowledge of algorithm development, particularly in a credit risk context.
• Proficiency in programming languages like Python, R, and SQL; familiarity with real-time data processing systems.
• Excellent analytical skills and attention to detail; ability to interpret complex datasets.
• Familiarity with global banking regulations and credit policies.