Collection Data Analyst
- We foster an INNOVATION mindset
- We achieve results with EFFICIENCY and excellence
- We take pride in the QUALITY of our work
- We uphold INTEGRITY in all we do
- We embrace COLLABORATION to work across business lines and borders
Job Description:
1. Collect, clean, and preprocess data from various sources to ensure accuracy and completeness.
2. Analyze and interpret complex datasets using statistical and data visualization techniques to identify potential risks and trends.
3. Collaborate with risk management teams to define risk metrics and develop models for assessing and quantifying risks.
4. Monitor and track Key Risk Indicators (KRIs) and key performance indicators (KPIs) to identify emerging risks and trends.
5. Produce comprehensive reports and presentations summarizing risk analysis findings for stakeholders and senior management.
6. Collaborate with IT teams to ensure data integrity, security, and compliance with data protection regulations.
7. Participate in the development and improvement of risk management strategies, policies, and procedures.
8. Stay updated on industry trends and best practices in risk management and data analysis.
Requirements:
1. Bachelor's degree in a relevant field such as Finance, Economics, Statistics, Mathematics, or Computer Science.
2. Proven experience (3+ years) in data analysis or a related field (Financial Technology is a plus, specialy on Collection Analytical Department).
3. Proficiency in data analysis tools such as Python, or SQL, and experience with data visualization tools (e.g., Tableau, Power BI).
4. Strong proficiency in Ms. Excel.
5. Knowledge of ISO 27001 is a plus point.
6. Familiarity with financial products, markets, and regulatory requirements is a plus.
7. Excellent analytical skills with the ability to work with complex, large datasets and draw actionable insights.
8. Strong communication skills to convey complex findings and insights to both technical and non-technical stakeholders.
9. Detail-oriented mindset with a focus on accuracy and precision in data analysis.
10. Ability to work collaboratively in cross-functional teams and adapt to changing priorities.
11. Problem-solving mindset and the ability to think critically and creatively to address emerging risks.
12. Professional certifications related to risk management or data analysis (e.g., FRM, CFA, CRMA) are desirable but not mandatory.
