As a Data Scientist in Enterprise AI (EAI), you will develop, deploy, and operationalize AI and GenAI capabilities across the Bank. You will collaborate with business and support units, contribute to AI/GenAI platforms, and drive the adoption of AI for measurable business impact.
Key Responsibilities:
AI & GenAI Solution Development
- Collaborate with data scientists, data engineers, and business/support units to evaluate, design, and deliver AI and GenAI-driven solutions.
- Develop performant AI and GenAI capabilities through research, experimentation, and prototyping.
- Develop and deploy AI and GenAI applications using agile prototyping methods.
- Integrate AI and GenAI solutions into the bank's ecosystem.
Project & Stakeholder Management
- Plan and execute AI initiatives aligned with strategic project and business objectives.
- Engage and manage stakeholder interactions and expectations.
- Provide advisory on AI and GenAI best practices to diverse stakeholders.
Research & Innovation
- Stay abreast of fast-emerging AI and GenAI technologies, tools, software, and industry best practices.
- Contribute to AI/GenAI validation, guardrail, and benchmarking exercises.
- Explore adjacent AI domains such as Agentic AI, Visual/Audio/Multimodal generation, and transformer/boosting models.
End-to-End AI Deployment
- Lead end-to-end LLM and AI solution deployment, ensuring high performance and scalability.
- Utilize Python, PyTorch, LangChain, and other AI/ML frameworks for solution development.
- Handle large datasets efficiently for AI model training and deployment.
Qualifications:
- Postgraduate degree in Statistics, Mathematics, Engineering, Computer Science, or related field; GenAI-related thesis/publications highly preferred.
- Minimum 5 years of advanced data science experience, preferably in banking, financial services, quantitative, or consulting domains.
- Proven track record in developing AI applications using transformer models, boosting models, and other advanced techniques.
- Demonstrable end-to-end LLM deployment experience of at least 1.5 years.
- Skilled in Python programming, large-scale data handling, and AI/ML packages (PyTorch, LangChain).
- Knowledge of agile project management practices.
- Experience with data visualization tools is a plus.
