AI Data Analyst/FS/12 months/Cantonese/40-55KHKD P/M

Data Professional with a strong AI/ML mindset to drive operational analytics across key Risk and Operations domains (Fraud, Collections, Underwriting, and KYC). This role bridges advanced data science and practical banking operations—turning complex business challenges into scalable, data-driven solutions, partnering with stakeholders across the bank, and ensuring high-standard delivery.

Principal Responsibilities

• Data Analysis & Insights: Analyze large volumes of structured and unstructured data to generate insights and recommendations across Risk and Operations (Fraud, Collections, Underwriting, KYC).
• Advanced Modeling: Apply advanced statistical techniques, predictive modeling, and AI/ML methods to develop practical, scalable solutions.
• Use Case Formulation: Proactively identify emerging business issues and priorities; translate them into analytics use cases with clear methodologies and measurable outcomes.
• End-to-End Delivery: Manage full-lifecycle delivery of analytics initiatives, including solution design, validation, performance tracking, and impact assessment.
• Stakeholder Collaboration: Partner with Business, Operations, and Technology teams to implement analytics/AI solutions and define performance measurement frameworks.
• Execution & Culture: Deliver high-quality outputs on time in a fast-changing environment, balancing rigor with pace, while sharing best practices to support a collaborative team culture.

Requirements

Experience & Education

• Education: University degree (or above) in Statistics, Mathematics, Computer Science, Data/Information Management, or a related quantitative discipline.
• Banking Experience: At least 6 years’ experience in retail banking analytics, including hands-on modeling and AI/ML application.
• Domain Expertise: Prior experience in risk-related domains (e.g., Fraud, Collections, Underwriting, KYC) is a strong advantage.

Technical Skills

• Core Stack: Strong track record of extracting insights from large datasets using Python and SQL/BigQuery.
• Cloud Infrastructure: Hands-on experience working in Google Cloud Platform (GCP) is strictly required.
• Data Visualization: Proficiency with visualization tools such as Tableau or QlikSense.

Language & Soft Skills

• Language Proficiency: Fluency in Cantonese and English is required to effectively collaborate with local operations teams and regional stakeholders.
• Communication: Strong communication skills with the ability to explain complex analysis clearly to varied audiences and influence decisions.
• Mindset: Proven ability to work effectively across business, operations, and tech stakeholders. High ownership mindset and a strong service orientation.

Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.