VP/SVP, Data Scientist, Technology & Operations Data Chapter, Group Transformation

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VP/SVP, Data Scientist, Technology & Operations Data Chapter, Group Transformation

Company Overview

A prominent financial services group in Asia, this institution is renowned for its comprehensive banking services, catering to consumer, SME, and corporate segments across Greater China, Southeast Asia, and South Asia. It has been consistently recognized for its financial strength, digital innovation, and contributions to society, creating impact beyond banking through social enterprise support and community skills development.

Role Overview

This Senior Data Scientist role is pivotal in advancing data-driven strategies within the Group Technology and Operations (T&O) Data Chapter. The individual will lead complex data science projects to enhance customer experiences and drive impactful decision-making aligned with the institution’s AI transformation strategy.

Key Responsibilities

1. AI/ML Development and Deployment
   • Design, develop, and deploy machine learning and generative AI models, supporting strategic priorities within T&O.
   • Establish scalable data science pipelines, driving impactful business outcomes across AI/ML initiatives.
2. Governance and AI Industrialization
   • Ensure rigorous model governance, including performance monitoring, validation, and recalibration.
   • Support AI industrialization through reusable components to streamline model deployment.
3. Collaboration and Industry Engagement
   • Collaborate with operations and technology stakeholders to prioritize data science initiatives.
   • Engage senior leadership to identify and implement data science opportunities with substantial business impact.

Key Requirements

• Educational Background
  • PhD or Master’s degree in computer science, engineering, mathematics, or related quantitative fields, particularly in machine learning, data mining, deep learning, or related areas.
• Professional Experience
  • Minimum 10 years in data science (banking, ecommerce, telecoms, retail, or technology) with a strong track record in research, innovation, and implementation.
  • Minimum 5 years with large datasets, using structured, semi-structured, and unstructured data to build and deploy machine learning models.
• Technical and Communication Skills
  • Proficiency in various AI/ML techniques, including classification, clustering, reinforcement learning, and NLP, with production deployment experience.
  • Familiarity with software development best practices; experience with generative AI models is a plus.
  • Strong stakeholder management and communication skills for effective cross-functional collaboration.

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