Data Scientist (VP/AVP) – AI Center of Excellence

About the role

BNP Paribas Wealth Management Asia is looking for a Data Scientist (VP/AVP) to help build, deploy and optimise AI models and to establish the Asia AI Center of Excellence under the Chief Digital & AI Officer. The role turns advanced AI and machine learning research into production-ready systems and integrates AI into the Wealth Management experience.

Key responsibilities

• Define, prioritise and execute the AI strategy, and identify technologies and partners for AI governance, tech stack, workflows, processes and standards
• Build the AI Center of Excellence and promote collaboration with other Group entities (CIB, AM and Retail banks)
• Develop machine learning models for credit risk scoring, churn prediction, portfolio optimisation, recommendation systems and next-best-action, and deploy them in production with engineers and IT
• Work with product owners, software engineers and business stakeholders on scalable ML pipelines for investment advisory, personalised recommendations, KYC/AML and other applications
• Collaborate with Front Office, Investment services, Sales, Marketing, Credit, Risk, Compliance and Operations to embed AI in client platforms, mobile apps and backend systems
• Mentor colleagues, upskill the workforce and foster a data-driven, AI-first mindset
• Ensure data quality, data governance and scalable data pipelines, and ensure AI applications meet regulatory and ethical requirements
• Monitor and optimise models continuously, and stay ahead of AI research advances

Required profile

• Master's or PhD in Computer Science, Data Science, Statistics, Applied Mathematics or a related field
• 3 to 7+ years of experience developing and deploying AI/ML models in production, preferably in financial services or technology
• Experience in AI for investment/portfolio analysis, recommendations or personalisation
• Good knowledge of Generative AI: prompt/context engineering, RAG, agentic AI, and understanding of data pipeline and architecture choices
• Knowledge of Agile, design thinking, test-and-learn and A/B testing
• Understanding of Wealth Management and financial services; Traditional and Simplified Chinese is an advantage

Required skills

• Machine learning frameworks such as TensorFlow, PyTorch and Scikit-learn, and libraries such as Pandas, Polars and NumPy
• Deep learning, NLP and/or time-series/econometric modelling
• Python, SQL and cloud platforms (AWS, Azure, Google Cloud, IBM); Docker, Kubernetes for deployment
• Gen-AI tools such as LangChain/LangGraph, vector databases and embedding models
• Model explainability and observability tools, CI/CD, MLOps/LLMOps, version control
• Preferred: AI CoE experience, AI-driven automation (chatbots, virtual assistants), data visualisation and prototyping