What is this position about?
• We are seeking a strategic, forward-thinking and impact-driven Data Scientist (Director level) to be a key contributor in our AI and Generative AI (GenAI) strategy & implementation.
• This role is a high-impact leadership role designed to bridge the gap between cutting-edge AI research and large-scale business implementation within Wealth Management Asia. This role is responsible for co-steering the roadmap of the AI Center of Excellence (CoE) while acting as a strategic navigator across the broader BNP Paribas organization.
• The successful candidate will combine deep technical mastery in Machine Learning and Generative AI with exceptional emotional intelligence (EQ) and organizational savvy. You will not only oversee the "how" of AI development but also the "why" and the "who"—ensuring that AI initiatives are aligned with business goals, culturally embraced by stakeholders, and successfully integrated into the bank’s complex regulatory and operational frameworks.
Key objectives of this role:
• 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
Your expertise will be crucial in shaping the AI strategy, developing advanced analytics models, and ensuring that AI technologies are embedded seamlessly into various client-facing and business functions. This is a chance to be part of a transformative journey as we set the foundation for AI-driven solutions in our Bank.
As a Data Scientist, you will collaborate with digital product owners and specialists, software engineers, and business stakeholders to develop scalable and robust machine learning pipelines and AI systems that power smart investment advisory, personalized recommendations, KYC/AML and other AI applications aimed at improving client outcomes and optimizing internal processes.
What would be your typical day at BNPP Paribas look like?
Primary Role Responsibilities
Strategic Steering & AI Center of Excellence Development:
• AI Strategy Leadership: Partner with the Chief Digital & AI Officer and senior leadership to define and execute an AI/GenAI strategy aligned with Wealth Management’s business goals.
• Use Case Orchestration: Identify, prioritize, and champion high-impact GenAI use cases (e.g., investment research synthesis, advisor enablement copilots, KYC document summarization, and hyper-personalized client engagement).
• Ecosystem Integration: Leverage the "One Bank" approach to develop collaborations with other Group entities (CIB, AM, and Retail) and optimize the reuse of common, standardized tech stacks.
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.
• Partner with engineering and data science to operationalize GenAI through secure APIs, model orchestration, and enterprise-grade architecture
• Lifecycle Management: Ensure end-to-end excellence in the AI lifecycle, from high-quality data strategy and scalable pipelines to continuous model monitoring and real-time optimization.
AI Model Development & Deployment:
Lead the design, development, and deployment of machine learning models, including deep learning, reinforcement learning, and natural language processing (NLP), to address business challenges in client segmentation, wealth management, fraud detection, and client experience optimization.
Collaboration Across Functions:
• Strategic Diplomacy: Act as a trusted advisor to senior leadership, translating technical potential into tangible business value and navigating the complex organizational dynamics of a global bank.
• Cross-Functional Integration: Work seamlessly with Front Office, Investment Services, Risk, Compliance, and Operations to embed AI solutions into client-facing platforms and backend systems to provide a cohesive experience across all touchpoints.
• AI Governance & Ethics: Partner with Legal, Risk, and Compliance to validate GenAI use cases, ensuring transparency, fairness, and strict adherence to data privacy and GDPR regulations.
• Cultural Transformation: Drive an "AI everywhere" mindset through mentorship, upskilling programs, and industry partnerships, fostering a culture of continuous innovation.
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.
• Promote AI literacy across the WM via industry partnerships particularly with tertiary institutions, training, documentation, and AI/GenAI fluency programs.
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.
• Establish GenAI-specific evaluation metrics such as toxicity, factuality, and response quality.
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.
• Partner with risk, legal, and compliance to validate GenAI use cases and maintain client trust.
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 Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Experience:
12+ years of experience in AI/ML, with at least 5-7 years in a senior or leadership role, preferably in financial services, banking, or technology sectors. Experience with AI implementation/industrialization in a client-centric environment (e.g., personalization, recommendations) is a strong advantage.
Good knowledge of agile methodologies, design thinking, Test &Learn & A/B testing approaches
Advanced Technical Expertise:
• Expertise: Deep knowledge of Machine Learning, Deep Learning, NLP, and Reinforcement Learning.
• GenAI Mastery: Strong command of LLM frameworks, Prompt Engineering, RAG, Vector Databases, and Agentic workflows.
• Engineering Fluency: Proficiency in Python, SQL, and cloud ecosystems (AWS/Azure/GCP), with a deep understanding of MLOps/ LLMOps and CI/CD.
• Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and libraries for model development.
• Deep expertise in deep learning, reinforcement learning, and natural language processing (NLP), particularly for developing recommendation systems and personalization models.
• Strong programming skills in Python, R, and SQL. Experience with big data technologies (Hadoop,
• Spark) and cloud platforms (AWS, Google Cloud, Azure).
• Expertise in building and optimizing end-to-end machine learning pipelines and managing model deployment at scale.
• Good knowledge in Generative AI specific skills: prompt engineering, RAG approaches, agentic AI, automated robustness and performance evaluation, production monitoring
Domain Knowledge:
Strong understanding of banking and financial services, with a focus on areas such as wealth
management, client behavior & analytics, risk management and fraud detection
Leadership & Collaboration (Critical):
• Proven ability to lead cross-functional teams and influence key stakeholders.
• Ability to inspire cross-functional teams and influence executive decision-making.
• Ability to read organizational dynamics, manage diverse personalities, and lead through influence rather than just authority.
• Strategic Communication: Exceptional ability to communicate complex technical concepts to C-suite executives and non-technical stakeholders into business value.
• Organizational Savvy: Ability to navigate a large, matrixed global organization to secure resources, alignment, and buy-in
Ethical & Regulatory Compliance:
Understanding of the ethical considerations of AI and its regulatory landscape in the financial sector.
Experience in ensuring models comply with data privacy and GDPR regulations.
Strategic Thinking:
Experience in defining AI strategies and embedding AI into an organization’s core functions. Ability to
assess business needs and translate them into actionable AI-driven solutions.
Preferred Skills:
• Familiarity with AI-driven automation for client service (e.g., chatbots, virtual assistants).
• Advanced data visualization skills using tools like Tableau, Power BI, or custom Python libraries (e.g.,Matplotlib, Seaborn).
• Thought leader in the AI community, ability to build relationships with regulators and tertiary institutions will be crucial.
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
