About UOBUnited 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.About the DepartmentThe Technology and Operations function is comprised of five teams of specialists with distinct capabilities: business partnership, technology, operations, risk governance and planning support and services. We work closely together to harness the power of technology to support our physical and digital banking services and operations. This includes developing, centralising and standardising technology systems as well as banking operations in Singapore and overseas branches.
Support T&O Risk Governance and Assurance function to develop and deliver data analytics solutions to further value-add in assurance reviews and other risk programs
Apply statistical tools/models to perform advanced data analytics and to identify/derive key insights from risk related datasets
Develop and implement artificial intelligence algorithms, rules and rapid prototypes from big data sets that will be fed into various risk/assurance programs
Perform deep-dive analysis to solve various business risk related problems
Design, build and automate intuitive dashboards that help to visualize, analyze, monitor key risk/performance metrics in order to answer complex risk related problems
University degree, preferably in computer science, engineering or analytical discipline, e.g. mathematics, statistics, IT, economics, finance, accounting. Master degree is preferred.
Proficiency across the core statistical toolsets (SQL, SAS, R, Python), data visualization tools (Tableau, Qlik, Power BI) and Hadoop ecosystem.
Knowledge of a variety of predictive models, machine learning algorithms and statistical techniques, e.g. logistic regression, decision tree, clustering, neural networks, support vector machines, principal component analytics, natural language processing.
In-depth knowledge of banking or technology processes, banking products and the overall industry a strong plus.
1-2 years working experience in data analytics or business intelligence units, preferably in financial industry.
Excellent communication skills (verbal, written) to deliver insights to senior management and stakeholders.
Analytical mind with ability to translate the business problems and requirements into analytics solutions.
Capability to dive deep into data to find answers to yet unknown questions and have a natural desire to go beneath the surface of a problem.
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