VP Analytic Models Platform Architect

7 months ago

Singapur, Singapore United Overseas Bank Full time

VP Analytic Models Platform Architect

Posting Date: 08-May-2023 Location:

Raffles Place, Singapore, Singapore

Company: 3677

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 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.

Job Responsibilities

Analytics Models Platform (AMP) Domain Data Architect

The AMP Architect will be responsible for designing, building and overseeing the overall AI and ML solution in organization. He/she will be the central point providing expertise on ML complexities around interconnectivity, integrations, privacy, security, scalability and operation. Main responsibilities will include:
• Architecting, designing, directing and leading AI and ML solutions that are scalable, fault-tolerant and low-bias and that can be integrated and operationalized using available tools and resources.
• Defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization. This includes decisions around leveraging open-source, augmented ML, pretrained ML models or integrated AI PaaS solutions.
• Establishing operational efficiency in AI initiatives by becoming the liaison with and developing a feedback loop between data science development and business use cases to ensure delivery of business value.

Job Requirements

Technical Skills 
• Have knowledge about Machine Learning and Data Science concepts, tools and automation processes.
• Have experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Know ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models managing and governing ML Models and managing and scaling AI platforms
• Be familiar with ML algorithms, AI use cases and applications. Should have an understanding of, but not expertise in, open-source high-code frameworks like PyTorch or TensorFlow, augmented AI and ML platforms, pretrained ML models and integrated AI PaaS tools.

Soft Skills
• Strong communication, teamwork and collaboration skills, working closely with software architects, data architects, data science teams and senior leadership
• Strong interpersonal skills to promote AI within the enterprise architecture.
• Leadership, delegation and technology management skills.
• Systems design thinking from a holistic perspective. 
• Strong strategizing and governance skills, planning long-term goals in partnership with senior management. 

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