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Company Overview
A leading bank in Asia, headquartered in Singapore, with a history dating back to 1935. Initially named United Chinese Bank, it was founded by a group of businessmen to serve the merchant community in Singapore amidst the economic uncertainties of the Great Depression. It was later renamed in 1965.
Job Title: VP, Data Scientist, Enterprise AI
Job Description
This role is a key member of Enterprise AI, focused on engaging with users to develop and deploy AI and Gen AI capabilities and applications for business and support units, ultimately delivering impactful outcomes.
Their main responsibilities include:
Collaborating with data scientists, data engineers, technology, and business/support units to evaluate, solution, and deliver AI and GenAI-driven business use cases.
Developing and successfully executing plans aligned with strategic project and business objectives.
Developing performant AI and Gen AI capabilities through thoughtful research and experimentation.
Developing and deploying AI and Gen AI applications with agile prototyping.
Integrating AI and Gen AI capabilities and applications into the organization’s ecosystem.
Staying abreast of fast-emerging AI and Gen AI technological advancements, industry best practices, architecture, software resources, and paradigms.
Engaging and managing stakeholder interactions and expectations.
Providing deep expertise and advisory on AI and Gen AI to diverse stakeholders.
Contributing to AI and Gen AI-related validation, guardrail, and benchmarking exercises.
Job Requirements
A minimum of a Postgraduate degree in Statistics, Mathematics, Engineering, Computer Science, or a related field, with the ability to reason quantitatively from first principles is required. GenAI-related thesis/publications are highly preferred.
A consistent record of success in framing rigorous and data-driven approaches to solve highly complex business use cases or academic problems is necessary.
The ideal candidate will possess a minimum of 5 years of advanced data science working or research experience, preferably within the banking, financial services, quant, or consulting industry.
They should be a self-motivated team player, capable of ideating innovative solutions and working independently.
A proven record in developing AI applications using transformer models, boosting models, and other advanced techniques is essential.
The candidate must be highly skilled and successful in end-to-end LLM deployment, with 1.5 years of full-time experience and demonstrable achievements.
Demonstrable expertise and experience in adjacent topics such as Agentic AI, Visual, Audio, and Multimodal generation is highly preferred.
Proficiency in Python programming and large data handling abilities is required, along with strong skills in common data science and LLM packages such as Pytorch and LangChain.
Experience in general end-to-end data science solution delivery and assorted tools is necessary.
The ability to communicate analytic findings clearly and convincingly to business stakeholders is crucial.
Skill in agile project management practices is required.
Experience with data visualization packages and/or tools is a plus.
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