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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.
About the Department The Credit and Risk Management function is comprised of three teams: Risk Management, Credit and Special Asset Management. We manage the risks arising from the Group's business activities within the risk appetite established by the Board. This involves identifying and evaluating the risks, developing effective risk governance and strategies as well as providing independent assessment of the overall risk profile.
Job Responsibilities The Role The role is based in Singapore and will be part of a team of over 40 analysts supporting Personal Financial Services (PFS), Business Banking (BB) and Private Banking (PB) business segments in Singapore and regionally.
Identify, initiate and lead data science / advanced analytics projects in the area of sales, marketing, CRM / customer engagement, risk, compliance and operational efficiency.
Leverage big data, machine learning and new technologies (voice, video, NLP, chatbot, etc) to support PFS, BB and PB management in achieving business KPIs - increase revenue (acquisition, advisory, cross-sell, attrition, pricing, etc), enhance customer engagement (sentiment analysis, call-centre, recommender engine, NPS, etc), reduce losses (alternative credit scoring, fraud, etc) and improve operational efficiency / effectiveness (optimization, RPA, OCR, visualization tools, etc)
Acquire, process and monetize internal and external data. This includes proactively sourcing for and working with external partners (fintechs, data providers, commercial entities and government agencies, etc)
Support end-to-end operationalization of analytic models. This includes generating requirements, testing and working with internal technology teams and external vendors
Continuously engage business managers and build relationships with internal and external stakeholders. Must be able to present / communicate complex concepts in simple terms / language, and translate data and models into actionable business insights
Relevant degree in Statistics / Computer Science, etc. MBA / post graduate degree is highly desired
More than 5 years of practical / commercial data science experience in a financial institution, fintech or other similar organizations. Must be equally comfortable in doing hands-on work as well as leading teams / junior colleagues
Extensive experience in Python, R and Scala on Hadoop / Spark big data pipeline (specifically, Cloudera platform for data engineering and data science). SAS and SQL experience also very useful. Cloud (AWS, Google, Azure) certification / experience is a bonus.
Analytical mind with sound business insight, excellent communicator (verbal and written), highly meticulous, and self-motivated
Maturity that will enable the candidate to be a credible counterpart to business managers and senior management, and the ability to develop on-going 'trusted advisor' relationships based on the ability to understand, analyse, discuss and address key business challenges raised
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