Data Scientist

Position Overview

BNP Paribas Wealth Management Asia is seeking a proficient Data Scientist (VP/AVP level) to contribute significantly to building, deploying, and refining AI models. This role is integral to launching the Asia AI Center of Excellence (COE) under the direction of the Chief Digital & AI Officer. The successful candidate will translate advanced AI and machine learning research into scalable production systems, driving innovation and embedding AI-based solutions within Wealth Management services.

Key Responsibilities

• Define and implement the AI strategy to maximize business value.
• Identify pivotal technologies and collaborators to establish robust AI governance.
• Develop technology infrastructure, workflows, procedures, and standards for AI development and production.
• Leverage the global BNP AI ecosystem to harmonize and reuse common standardized technology components.
• Collaborate cross-entity with Corporate & Investment Banking, Asset Management, and Retail banking divisions under a unified "One Bank" approach.
• Promote an organizational culture embracing analytics and AI accessibility for all wealth management staff.
• Work alongside digital product teams, software engineers, and business units to create robust machine learning pipelines supporting investment advisory, personalized recommendations, KYC/AML, and other AI-driven applications.
• Lead the development and expansion of the AI Center of Excellence, ensuring strategic direction, governance, and ethical AI use aligned with digital transformation goals.
• Develop and deploy AI-driven initiatives including predictive analytics for client behavior, market trends, credit risk scoring, churn prediction, and portfolio optimization.
• Design and operationalize models for personalized investment journeys, client engagement, and automated processes like KYC and credit management.
• Integrate AI solutions across diverse teams including Front Office, Sales, Credit, and Compliance to ensure seamless technology embedding within platforms and applications.
• Mentor peers and foster ongoing innovation, knowledge sharing, and workforce upskilling in AI capabilities.
• Ensure data quality through best practices in data collection, cleaning, and governance, collaborating with data teams for scalable pipelines.
• Guarantee AI compliance with regulations and ethical standards, working closely with legal and compliance teams to maintain transparency and fairness.
• Implement ongoing monitoring and tuning of AI models to adapt to changing business and market dynamics.
• Remain current with advances in AI research to enhance fraud detection, personalization, and other banking AI applications.

Qualifications

• Master’s or PhD degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related fields.
• Between 3 to over 7 years of hands-on AI/ML experience, including production deployment, preferably within financial services or technology sectors.
• Experience in AI applications for investment strategies, portfolio optimization, recommendation systems, and personalization.
• Proficiency in Generative AI concepts including prompt engineering, retrieval augmented generation (RAG), agent-based AI, understanding of data pipelines and architectures, automated model robustness and performance monitoring.
• Familiarity with agile frameworks, design thinking, experimental Test & Learn, and A/B testing approaches.
• Technical expertise in machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, Pandas, Polars, and Numpy.
• Strong capabilities in machine learning, deep learning, natural language processing, and time-series or econometric modeling relevant to recommendation systems, pricing personalization, portfolio simulation, risk and impact analysis, and workflow automation for client services and compliance.
• Programming proficiency in Python and SQL, experience with cloud platforms including AWS, Azure, Google Cloud, IBM, plus containerization and orchestration tools like Docker and Kubernetes for scalable deployment.
• Knowledge of Gen-AI tooling and frameworks, including prompt engineering, text-to-SQL, vector databases, embedding models, LangChain/LangGraph, and multi-context processing.
• Understanding of model explainability and observability best practices for transparency.
• Experience managing end-to-end AI model lifecycle, version control systems, CI/CD pipelines, and MLOps/LLMOps practices.
• Domain insight into Wealth Management, risk management, fraud detection, and client analytics advantageous.
• Strong problem-solving skills with a creative approach to delivering innovative business-centric AI solutions.
• Excellent collaboration and communication skills to interface with cross-functional teams and translate complex technical concepts to non-technical stakeholders.
• Proficiency in Traditional and Simplified Chinese is a plus.

Preferred Experience

• Experience establishing or working within an AI Center of Excellence.
• Development of AI-powered automation such as chatbots and virtual assistants for client servicing.
• Familiarity with AI agent frameworks and tooling.
• Capabilities in data storytelling, visualization, and rapid prototyping.

About BNP Paribas

BNP Paribas is a premier European Union bank and among the world’s largest financial institutions, present in the Asia-Pacific region since 1860. The bank provides extensive financial services across corporate, institutional, private investors, asset management, and insurance sectors.

Committed to diversity and inclusion, BNP Paribas actively fosters an inclusive work environment welcoming applicants of all backgrounds, including those with disabilities and diverse gender identities and orientations. Internal networks support LGBTQIA+ community members, gender representation, employees with disabilities, and cultural diversity.

The bank is dedicated to sustainability and has pledged to finance a carbon-neutral economy by 2050, being a founding member of the Net-Zero Banking Alliance and actively supporting clients’ transitions to low-carbon pathways.