Data Scientist (VP/AVP)

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Senior Data Scientist role driving AI strategy and model deployment at BNP Paribas Wealth Management in Singapore.

Lead AI Center of Excellence, mentorship, and cutting‑edge AI research in finance, with strong focus on compliance and ethics.

What is this position about?

We are looking for a skilled Data Scientist (VP/AVP) to join our team at BNP Paribas Wealth Management Asia to play a critical role in building, deploying, and optimizing AI models. This is an exciting opportunity to play a pivotal role in establishing our Asia AI Center of Excellence (COE) under the leadership of the Chief Digital & AI Officer. You will be responsible for translating advanced AI and machine learning research into production‑ready systems, enhancing the bank's ability to drive data‑centric innovations, and integrating AI‑driven solutions into the Wealth Management experience with the following key objectives:

• Define, prioritize & execute our AI strategy & plan, Maximize AI’s value creation
• Identify key technologies & partners to design & implement the entity’s AI governance,
• Build its tech stack, workflows, processes & standards for development & industrialization
• Leverage the Group AI ecosystem to optimize synergies & re‑use of common, standardized tech stacks
• Under a “One Bank” approach, develop collaborations with other Group entities (CIB, AM & Retail banks).
• Promote a “analytics” & “AI everywhere, for everyone” mindset for all BNPP Wealth Management staff

Primary Role Responsibilities

• AI Center of Excellence Development:
  Partner with senior leadership to build and expand the AI Center of Excellence (COE), setting the strategic direction and driving AI adoption across the bank. Champion best practices, governance, and ethical AI frameworks, ensuring that AI initiatives align with the bank’s broader digital transformation objectives.
• Industrialization of our AI Priorities:
  Drive AI‑powered initiatives by developing advanced machine learning models that tailor banking services and financial advice to the unique preferences, behaviors, and needs of each client and staff. Utilize predictive analytics to forecast client behaviors, market trends, and potential risks. Build advanced models for credit risk scoring, churn prediction, and portfolio optimization that enable proactive decision‑making and enhance financial outcomes. Leverage deep learning, recommender systems, and predictive analytics to deliver individualized experiences that improve overall satisfaction and loyalty.
• Model Development and Deployment:
  Design, develop, and deploy AI models that enable tailored investment journeys, optimized and hyper‑personalized client interaction and engagement, and smart automation of complex processes e.g. KYC and Credit. Work with engineers and IT to deploy models into production, ensuring models run reliably and efficiently at scale within the bank’s ecosystem in production.
• Collaboration Across Functions:
  Work cross‑functionally with teams in Front Office, Investment services, Sales Management & Marketing, Credit, Control functions (Risk, Compliance, Operations etc.) to integrate AI solutions into various daily activities. Ensure that AI models are seamlessly embedded into client‑facing platforms, mobile applications, and backend systems to provide a cohesive experience across all touchpoints..
• Leadership and Mentorship:
  Provide mentorship and foster a culture of innovation, knowledge‑sharing, and continuous learning with peers & colleagues. Bring the entire workforce on the journey of AI for upskilling/ re‑skilling.
• Data Strategy & Data Quality:
  Ensure that high‑quality, accurate, and reliable data is available for building AI models. Establish best practices for data collection, data cleaning, and data governance. Collaborate with other data‑related functions to build scalable data pipelines for model training and deployment.
• AI Ethics & Compliance:
  Ensure that AI applications comply with regulatory requirements and ethical standards, particularly in the context of Wealth Management, where sensitive client data and privacy concerns are paramount. Work with legal and compliance teams to ensure transparency, fairness, and accountability in AI model outputs.
• Continuous Model Monitoring & Optimization:
  Implement robust monitoring systems to track the performance of AI models and adjust for evolving client needs, business requirements, and market conditions. Optimize models in real‑time based on feedback loops and ongoing performance data.
• Innovation & Research:
  Stay abreast of the latest advancements in AI, machine learning, and data science research. Apply cutting‑edge techniques to further improve personalization algorithms, fraud detection, and other AI‑powered banking solutions.

What is required for you to succeed?

Education

Master’s or PhD in Computer Science, Data Science, Statistics, Applied Mathematics or a related field.

Experience

3 to 7+ years of experience in AI/ML with hands‑on experience in developing and deploying AI models into production, preferably in the financial services or technology sector. Experience in AI for investment/portfolio analysis and optimization, OR recommendations systems and personalization. Good knowledge to expertise in Generative AI specific skills: prompt/context engineering, various RAG approaches, agentic AI, ability to understand & challenge data pipelines & architecture choices, anticipate key stakes in robustness and automated performance evaluation / prod monitoring. Good knowledge of agile methodologies, design thinking, Test&Learn & A/B testing approaches.

Technical Skills

o Expertise in machine learning frameworks such as TensorFlow, PyTorch, Sklearn and relevant libraries like Pandas, Polars, Numpy o Expertise in Machine Learning, Deep Learning, NLP, and/or Time-series / Econometric modeling for one or more of the following applications: • Recommendation systems, Next Best Action, Pricing and personalization (particularly translation) • Portfolio simulation and optimization, investment scenario modeling, risk and impact analysis • Automation / augmentation of client service and/or credit, compliance (e.g. KYC, AML), or other operational processes o Strong programming skills in Python, SQL and experience with cloud platforms (AWS, Azure, Google Cloud, IBM) and tools like Docker, Kubernetes/ K8s for model deployment. o Experience in Gen-AI applications such as prompt engineering and optimization, RAG, text-to-SQL and related frameworks/tooling e.g. vector databases, embedding models, langchain/langgraph, MCP. o Good knowledge/experience with model/LLM explainability and observability tools o Experience in end‑to‑end AI model development and deployment at scale, version control, CI/CD practice, and MLOps/LLMOps tooling.

Domain Knowledge

Understanding of Wealth Management and financial services, with experience in areas such as risk management, fraud detection, wealth management, and client analytics is beneficial.

Problem‑Solving & Innovation

Ability to think critically and creatively to solve complex problems and build innovative machine learning solutions that drive business value.

Collaboration & Communication

Strong teamwork skills and the ability to collaborate effectively with cross‑functional teams. Excellent communication skills to explain technical concepts and outcomes to non‑technical stakeholders.

Proficiency in both Traditional and Simplified Chinese would be an advantage

Preferred Skills

• Experience in setting up or working within an AI Center of Excellence (CoE)
• Experience building AI-driven automation for client service (eg chatbots, virtual assistants)
• Familiarity with AI agent frameworks and tools
• Data storytelling through advanced visualization and quick prototyping

About BNP PARIBAS

As the leading European Union bank, and one of the world’s largest financial institutions with an uninterrupted presence in the region since 1860, BNP Paribas offers a wide range of financial services for corporate, institutional and private investors spanning corporate and institutional banking, wealth management, asset management and insurance.

We passionately embrace diversity and are committed to fostering an inclusive workplace where all employees are valued and encourage applicants of all backgrounds, including diversity of origin, age, gender, sexual orientation, gender identity, religion applicants who may be living with a disability. We have a number of internal employee networks in place to empower our staff to act and challenge the status quo.

• BNP Paribas PRIDE is highly active in favour of the LGBTQIA+ community
• BNP Paribas MixCity which fosters better representation of women at all levels of the organization
• Ability, the mutual aid network for employees with a disability or a disabling or chronic illness
• BNP Paribas CulturAll which celebrates diverse backgrounds

BNP is committed to financing a carbon‑neutral economy by 2050. The Group is a founding member of the Net‑Zero Banking Alliance and has set up its own Low Carbon Transition Group to support its clients through their energy transitions.

https://careers.apac.bnpparibas/

More information 

BNP Paribas - Diversity & Inclusion Journey

BNP Paribas - The Bank Of Green Changes

Award Obtained

BNPP has won Top employer Europe award in a 10th consecutive year