AI Business Analyst

TSS; Hong Kong; On-site; HKD 420,000 - 600,000; Full time

Job summary

TSS in Hong Kong seeks an AI Business Analyst to bridge business stakeholders and technology teams, identifying and evaluating AI, ML, and data-driven solutions to optimise banking processes and customer experiences.

Responsibilities include gathering requirements with various banking units, translating into technical specs, developing use cases, mapping workflows, coordinating UAT, and ensuring governance and regulatory alignment with data privacy policies.

Qualifications

• Bachelor's degree in a relevant field.
• 3+ years of experience as a BA, Data Analyst, or PO in banking/fintech.
• Experience delivering data analytics, automation, or AI/ML initiatives.

Responsibilities

• Requirements gathering with business units (retail, commercial, risk, operations) to identify AI value.
• Translate business requirements into technical specs and user stories for data science/AI teams.
• Develop use cases with feasibility studies and ROI projections for AI initiatives.
• Analyze current workflows and design AI-integrated processes to improve efficiency and reduce turnaround times.
• Coordinate UAT and ensure AI solutions meet business objectives and quality standards.
• Ensure AI initiatives comply with local regulations, data privacy laws, and internal risk policies.

Skills

SQL

Excel

Python/R

Education

Bachelor's degree

Tools

Jira

Confluence

Job description

We are representing a prominent, long-standing commercial bank committed to driving digital transformation and innovation across its banking operations. They are seeking a strategic and analytical AI Business Analyst to bridge the gap between business stakeholders and technology teams. In this role, you will help identify, evaluate, and implement artificial intelligence, machine learning, and data-driven solutions to optimize banking processes, elevate customer experiences, and strengthen risk and compliance frameworks.

Key Responsibilities

Requirements Gathering & Analysis: Collaborate closely with business units (such as retail banking, commercial banking, risk management, and operations) to understand their operational challenges and identify opportunities where AI can add measurable value.

Bridge Business & Tech: Translate complex business requirements into clear, functional technical specifications and user stories for data science and AI engineering teams.

Use Case Development: Conduct feasibility studies, cost-benefit analyses, and ROI projections for proposed AI initiatives, machine learning models, and automation projects.

Process Mapping & Workflow Optimization: Analyze current operational workflows and design streamlined, AI-integrated processes to improve efficiency and reduce turnaround times.

Testing & Quality Assurance: Partner with stakeholders to define acceptance criteria, coordinate User Acceptance Testing (UAT), and validate that deployed AI solutions meet business objectives and quality standards.

Governance & Compliance Alignment: Ensure all AI and data initiatives comply with local regulatory standards, data privacy laws, and internal risk management policies.

Qualifications & Requirements

Education: Bachelor’s degree in Business Administration, Finance, Computer Science, Information Systems, Data Analytics, or a related discipline.

Experience:

3+ years of experience as a Business Analyst, Data Analyst, or Product Owner, preferably within the banking, financial services, or fintech sector.

Proven track record of participating in the end-to-end delivery of technology projects, ideally involving data analytics, automation, or AI/ML solutions.

Technical & Analytical Skills:

Strong proficiency in data analysis tools and querying languages (e.g., SQL, Excel, Python/R for data exploration is a plus).

Familiarity with Agile/Scrum methodologies, user story creation, and backlog management tools (e.g., Jira, Confluence).

Good understanding of AI concepts (such as Generative AI, machine learning, Natural Language Processing, or intelligent automation) and their practical applications in finance.

Soft Skills: Exceptional stakeholder management and communication skills, with fluency in English and Cantonese (Mandarin is a strong plus) to liaise effectively with regional and local teams.