AVP, Data Scientist (Global Markets), Data Management Office

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 Data Management Office and Analytics Transformation Office function answers the demand for quality and credible data across the Group.
 
Data Management Office
We govern the use of data across the Group and provide guidance for data management and usage. This optimises the value of data to enable smarter, faster and more accurate decision-making as well as improve operational efficiency. Above all, we ensure adherence to all data governance standards as determined by regulators.

Analytics Transformation Office
We are a centralised analytics function that supports Group-wide business units and their analytical needs. We aim to establish ourselves as an analytics centre of excellence and drive analytics adoption and the utilisation of new big data technology across the Group. Our key areas of service range from business intelligence, strategic analytics to data science.

Job Responsibilities

The role is a key member of Enterprise AI to engage with users, to develop and deploy Portfolio and Econometrics (P&E) capabilities and applications, for business and support units, and deliver impactful outcomes.

The Bank portfolio holds assets and liabilities across diverse instruments, geographies, client segments and products, which can in turn be classified into market tradable and non-market tradable instruments. Developing a suite of complementary portfolio and econometrics modelling, forecasting, management and optimization capabilities enables data science driven strategic planning, scenario analysis, forecasting and optimized portfolio shaping in a holistic, optimal, timely, systematic and explainable manner. 

Your main responsibilities are to:

• Collaborate with data scientists, data engineers, technology and business/support units, to evaluate, solution and deliver P&E driven business use cases.
• Develop and successfully execute plans aligned with strategic project and business objectives.
• Develop performant P&E capabilities through thoughtful research and experimentation.   
• Develop and deploy P&E applications with agile prototyping.
• Integrate P&E capabilities and applications into the bank's ecosystem.
• Stay abreast of fast emerging AI SOTA technological advancements, industry best practices, architecture, software resources and paradigms.
• Engage and manage stakeholder interactions and expectations. 
• Provide deep expertise and advisory on P&E to diverse stakeholders.
• Contribute to P&E related benchmarking exercises.
• Enrich skillsets and increase exposure for our data scientists, each will also contribute in a secondary and significant task, in this case on GenAI capabilities delivery.

Job Requirements

• Min Postgraduate degree in Statistics, Mathematics, Engineering, Computer Science or a related field, with ability to reason quantitatively from first principles. AI related thesis/publications on P&E topics highly preferred.
• Achieved consistent success in framing rigorous and data driven approaches to solve highly complex business use cases or academic problems.
• Min 5 years of advanced data science working or research experience, preferably in banking / financial services / quant / consulting industry. 
• Self motivated team player, able to ideate innovative solutions and work independently. 
• Highly skilled and successful in end-to-end Portfolio Optimization or Econometrics deployment, with 1.5 years full-time experience. Demonstrable achievements is a must.  
• Strong and demonstrable expertise and experience in Deep Learning a must.
• Demonstrable expertise and experience in adjacent topics such as Reinforcement Learning, Causal Inferencing, Probabilistic Bayesian, advanced Econometric Modelling highly preferred.
• Passion and some expertise and experience in GenAI such as LLM, Multimodal highly preferred.
• Python programming and large data handling abilities. Highly skilled with common data science packages such as Pytorch and Market Optimization/Forecasting related packages.
• Experienced in general end-to-end data science solution delivery and assorted tools.
• Ability to communicate analytic findings clearly and convincingly to business.
• Skillful in agile project management practices.
• Experience with data visualization packages and/or tools a plus.

Be a part of UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's 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.

Apply now and make a difference.