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Job Title

Financial Crimes Compliance – Data Scientist

Job Description

RHB Bank was established in Singapore in 1961 and, through a series of rapid expansion and strategic mergers, became known as RHB Bank Berhad Singapore (RHBS) in 1999. As a fully-licensed bank, throughout these years of dedication in Singapore, we have certainly built formidable ties with our customers and established ourselves as one of the Republic’s most trusted financial institutions.

RHB Bank Singapore opens doors to new opportunities. We are expanding regionally and are currently looking for a Financial Crimes Compliance Data Scientist to be part of our AML Compliance department.

You will be part of the team, honing your skills to be a full-fledged Data Scientist/Analyst by working closely with the Head of Departments and the team.

The role will be the Data Science subject matter expert for the AML & Sanctions Compliance department in using technology (Machine Learning/RPA/Artificial Intelligence and Advanced Analytics) to:

  • Enhance workflow within and across teams by reducing manual and duplicated tasks.
  • Implement automated solutions that will embody Machine Learning, AI, RPA, Vision and Advanced Data Analytics.
  • Implement and maintain visual stories and dashboards for AML reporting and data analysis.
  • Implement statistical and analytical tuning and optimization of AML detection scenarios, matching algorithms and client AML risk segmentation.
  • Apply machine learning and use it as a core component of Financial Crimes Compliance Framework.
  • Work with upstream teams to integrate various systems and data sources within the Bank for achieving efficiencies in cost and productivity of the AML team.
  • Deliver solutions and improve compliance control framework around tracking solutions, monitoring solution, and testing the effectiveness of controls.
  • Collaborate with other stakeholders to drive the transformation process in Compliance.
  • Development and implementation of New Compliance Processes, Controls, Systems and Strategy.
  • Implement and execute Data Quality controls and monitoring across financial crimes compliance functions.
  • Drive and deliver AML data initiatives and AML Risk Assessment outcomes to regulators (e.g. MAS and BNM).
  • Evaluate and test transaction monitoring scenarios and matching rules through analytics on a periodic basis.
  • Generate compelling visual stories to front line and banks management depicting AML trends and risk being detected on an ongoing basis.
  • Be an all things data person for AML teams and solve data challenges by collaborating with team leads across various functions in AML department (Enhanced Due-diligence, Risk Assessment, Transaction Monitoring, Transaction Screening, Name Screening, Payments Advisory, Assurance & Controls, Policy & Training, Trade Finance AML, ABC, FM Surveillance and Systems).


  • Master’s degree or Bachelor's degree in Engineering, Mathematics, Statistics, Data Science and Computer Science preferred.
  • At least 5 years of experience working in Data Science, Advanced analytics and Statistics (Candidates with lesser experience will also be considered if they have an impeccable academic application of Data Science along with published projects in Data Science).
  • Experience in Big Data processing, NLP, Computer Vision, Data articulation, cleansing and visualization.
  • Experience with machine learning frameworks (like Tensorflow or PyTorch) and libraries (like scikit-learn, pandas numpy).
  • Understanding and data science applicable expertise with statistics and probability.
  • Advanced competency and expertise in Modelling & Machine Learning Techniques (LightGBM, XGBoost, ensemble, stacking methods, regression, decision tree models, survival analysis, cluster analysis, forecasting, anomaly detection, association rules, neural networks, sentiment analysis and SVMs etc.) with exposure and experience in additional techniques.
  • Advanced competency and expertise in at least one Data ETL (Teradata, Oracle, SQL, Python, Java, Ruby, Pig) with exposure and business-applicable experience in additional languages.
  • Experience training ML models in cloud computing environments such as: Amazon EC2, Google Cloud Platform, Microsoft Azure, etc.
  • Experience in AWS (Redshift, S3, EC2, EMR, etc.) will be advantageous.
  • Experience in SQL and in at least one scripting language (Python/R/Java etc.)
  • Knowledge in graph database (Amazon Neptune, Gephi, Neo4j, Titan, Apache Graph etc.) and graph analytics will be advantageous (or at least have passion to learn and apply).
  • Self-driven, highly motivated, thrive on challenges and able to work as a team player.
  • General understanding of Anti Money Laundering, Sanctions Compliance and MAS regulatory requirements (e.g. MAS 626) is an added advantage but not required.

Experience Level

Mid-Senior Level

Interested? Apply Now!

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