Data Analyst - Financial Crime Compliance (Manager)

Besides attractive remuneration packages, we offer non-financial benefits and opportunities to develop your potential within OCBC Group’s global network of subsidiaries and offices. If you have passion, drive and the

At Bank of Singapore, we are constantly on the lookout for exceptional individuals to join our team. We promote a culture of openness, teamwork and fairness. Most importantly, we invest in our people through our programmes that develop them on both professional and personal levels.

• financial benefits and opportunities to develop your potential within OCBC Group’s global network of subsidiaries and offices.

• Implement automated solutions using Python to automate manual processes in data collection, data transformation and data aggregation to generate analytical, regulatory and management reports.
• Build and maintain dashboards using data visualization tools such as Power BI to drive a data driven Financial Crime Compliance organization.
• Work with the Bank Data Hub to develop use cases for reporting, dashboard creation and data analysis
• Collaborate with IT Project Team to integrate AI Models and Analytics solution into the Compliance Front-End platform.
• Act as Data & Analytics Steward to provide guidance and advice to Compliance SME on using data at the core of their business decision so as to drive Financial Crime Complaicne from a data driven to AI-drive function.
• Experiment with Generative AI to drive risk efficiency and risk effectiveness.

• At least 3 year experience in developing data analytics solution, machine learning models or Generative AI.
• Degree holder in relevant fields (i.e.

• Experience in design, development and implementation of data analytics solution using Python and data visualization tools such as Power BI / Qlikview / Tableau.
• Experience in data model design to build scalable and robust data platform to support data analytics and AI solutions.
• Good knowledge in statistical analysis, data mining and processing, decision tree design, clustering, knowledge of SQL, Python or other analytics tools are essential.
• Good knowledge in Artificial Intelligence based predictive algorithm, Machine Learning, Natural Language Processing (NLP), data science and data mining.
• Ability to work with unstructured data, parallel databases and parallel query processing.