About UOB
United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.
Job Description
- Develop machine learning models and analytics-driven methodology to generate actionable insights, especially in Anti-Financial Crime (AFC) / AML risk identification, assessment and monitoring.
- Provide data analytics including data visualization, report generation and automation to support and accelerate various AML risk initiatives.
- Periodic review on model/analytics input, output, structure and criteria.
- Enhance and build data assets for Wholesale Banking in accordance to business needs and Banks policy.
Requirements:
- Proficient in programming language of Python/R and SQL
- Skilled in data mining, machine learning and data visualization
- Experience in AML space is an advantage
- Experience in building dashboard through Qlik Sense or similar tools
- Experience in Wholesale Banking segment is preferred
Additional Requirements
Develop, Engage, Execute, Strategise
Be a Part of the UOB Family
UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate&aposs age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.
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