Job Description:
Development and implementation of advanced analytics models to optimize the efficiency and effectiveness of the Group Regulatory Compliance monitoring program in fighting financial crime.
Accountabilities and Key Roles :
- Develop predictive analytics and machine learning algorithms to capture and mitigate the risk of Money Laundering, Financial Crime, and Sanctions.
- Apply the best possible combination of explanatory analysis for feature extraction, visualization, data engineering, and machine learning to the area of combatting financial crime.
- Develop all phases required in the predictive model delivery lifecycle, inclusive of data extraction and transformation, data explanatory and statistical analysis, algorithm development, tuning, and testing.
- Closely collaborate with Financial Crime and AML stakeholders to translate money laundering methods into predictive analytical models.
- Work with complex datasets, and generate GRC insights & visualizations for both technical and non-technical audiences.
- Conduct deep dives into Financial Crime and AML systems to identify key business opportunities.
Experience:
- Up to 7 years of relevant experience in data science / machine learning domain (must).
- Business Intelligence, Data Warehousing & Dimensional Modelling, Data Wrangling & Preparation.
- Python, SQL programming.
- BI tools, i.e. Tableau, Power BI.
Education:
- University degree from a recognized university in Data Science, MIS, BIS, or computer science.
- Any certification in data science, Python/R, SQL, and BI tools is a plus.
Competencies:
- Analytical skills and proven ability to think out-of-the-box.
- Good understanding of GRC.
- Presentation, communication & interpersonal skills.
- Fluent in English and in Arabic.
