- Develop and implement advanced statistical models and machine learning algorithms to
- solve complex financial problems.
- Analyze large and complex financial datasets to identify trends, patterns, and
- opportunities for increased controls and enhanced risk mitigation.
- Build predictive data models for risk assessment.
- Forecast, track, and measure key metrics.
- Collaborating with IT and finance teams to translate data insights into actionable
- strategies and initiatives to implement.
- Staying current on financial industry best practices and emerging risk factors.
- Conducting regular security audits and penetration testing.
- Analyzing security incidents and implementing corrective actions
Preferred Qualifications:
- Experience in financial services industry retail banking products
- Experience in data analysis and financial risk management
- Knowledge of forensic financial auditing techniques.
- Proficiency in scripting and programming languages (e.g., Python, Bash, SQL)
- Understanding of network security, encryption and access control principles.
- Knowledge of machine learning and data analytics.
- Relevant certifications such as CDA, CRMA or similar are highly desirable