Senior/ Junior Business Data Analyst (AI products)

Job Holder will:
Act as a bridge between business stakeholders and Data & AI solution development teams to shape, propose, and validate the most appropriate use of AI for specific business contexts.
Be accountable for translating business objectives and requirements into analytical logic and feasible, governed AI solutions, ensuring solutions are delivered for the right purpose, create measurable value, and comply with data governance, risk, and operational requirements.
Participate directly in the implementation and handover of technology solutions leveraging AI on big data platforms to support business use cases.
Possess sufficient technical foundation to work directly with technical teams (Data/AI/Engineering) to assess solution feasibility, data readiness, and system integration.
Key Accountabilities (1)
A. Research and analysis
Analyze and clarify business problems in specific contexts; define business objectives, analytical hypotheses, and success criteria for AI solutions.
Identify required data entities, attributes, and data sources to validate hypotheses and build appropriate AI solutions.
Participate in analysis, data preparation, and evaluation of AI models/solutions from a business perspective, including interpreting outputs, identifying limitations, risks, and the real value AI delivers.
Visualize and align early product concepts with business and technical teams through initial designs and prototypes (Prototyping) using Vibe Coding/GenAI.
Propose ideas and approaches for data products and AI solutions, including building MVPs.
Key Accountabilities (2)
B. Reporting & Documentation
Collaborate with PO and business units to clarify requirements, business assumptions, and evaluation criteria across documents, templates, and work management tools.
Create and complete specifications related to data and processing logic to ensure AI solutions are implemented within the agreed business scope and objectives.
Build and maintain KPI/metrics frameworks to evaluate the effectiveness of AI solutions post-deployment, supporting ongoing tracking, evaluation, and continuous improvement.
Improve the quality of templates, checklists, and processes to ensure documentation reflects the correct business intent and how AI is used.
Key Accountabilities (3)
C. Stakeholders collaboration & management
Work with Consulting/Design/Delivery functions (e.g., Architect, AAI, Development) to evaluate, define, and directly build technical solutions applying AI technologies to data-driven business problems.
Collaborate with AI Engineers for scenarios requiring large-scale automation, ensuring focus on business logic, orchestration, and control, while AI Engineers own architecture and scalability.
Partner with business units to validate and verify outcomes from customized AI solutions for specific needs.
Deliver training and support to business units to help them understand and use AI solutions effectively.
SUCCESS PROFILE REQUIREMENTS
Qualifications and Work Experience
Qualifications
Bachelor's degree in IT/Computer Science, Banking & Finance, or related fields.
Working Experience
4+ years' experience in a Business Analyst / Senior Business Analyst. Including 2+ years' experience in Financial Institutions with Data warehousing and reporting
3+ years' experience with Cloud Platform (AWS, Azure, Google Cloud) & with 1+ years' on AWS and/or Data Brick
1+ year's experience developing & deploying AI solutions, products
Proficient in querying, visualizing data using SQL, Python languages by using data programming tools and data visualization techniques
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Able to work independently with minimum supervision.
Strong verbal and written communication skills.
Foreign language
English Level 3 (TOEIC = 650 - 699) / or according to TCB's regulations in each period
Preferred
Experience with cloud platforms (AWS, Azure, Google Cloud), especially AWS or Databricks.
Proficiency in querying data using SQL and Python; familiar with data programming tools and data visualization techniques.
Use of Gen AI tools to support daily work tasks.
Software development experience, especially in AI/ Gen AI applications.