Technical Business Analyst – AI Transformation

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 900,000 - 1,400,000; Full time

Benefits offered by this job

Restaurant d'entreprise

Indemnités de stage/alternance

Job summary

Randstad Hong Kong Limited is seeking an experienced AI/GenAI Risk Product Manager/Business Analyst to drive end-to-end risk projects. You will bridge Risk leadership with Data Science and Cloud Engineering, evaluating use cases for feasibility, costs, and ROI while leading discovery workshops and PoCs.

The role requires 8+ years in financial services risk, strong Python/SQL data skills, and proficiency with AWS, Azure or GCP.

Qualifications

• 8+ years in Financial Services risk analytics, with agile delivery experience.
• Strong data exploration with Python and SQL in project contexts.
• Experience with AI/GenAI risk use cases and PoCs.

Responsibilities

• Drive end-to-end delivery of AI/LLM risk projects, bridging Risk leadership, Data Science and Cloud Engineering.
• Evaluate AI/LLM use cases for feasibility, compute costs, ROI and resources.
• Lead workshops to identify GenAI/ML opportunities for process optimization and automation.
• Manage backlogs, map user journeys, and write granular technical user stories with acceptance criteria.
• Oversee PoC activities, validate model performance, and present results to executives.
• Build business cases, define benefits realization frameworks, and track KPIs.
• Collaborate with AI and data teams to run prototype data queries in Python and SQL.
• Document regulatory governance and audit trails for enterprise AI adoption.
• Support migration, testing, and deployment of risk analytics models on Cloud platforms.

Skills

Agile project management

Backlog prioritization

User story creation

Python

SQL

GenAI / ML

Cloud platforms (AWS/Azure/GCP)

Stakeholder management

Education

Bachelor's or Master's in CS / Quant / Data Science

Tools

AWS

Azure

GCP

Job description

about the company.

Our client is a premier global life insurance and financial services group in Hong Kong with a major Asia-Pacific footprint. They invest heavily in digital transformation, cloud migrations, and cutting-edge artificial intelligence, building scalable, compliant, and data-driven risk management infrastructure to support regional growth and enterprise security.

about the team.

You will join the Regional Risk Management transformation team, working at the intersection of risk policy, data engineering, and quantitative science. The team culture is highly technical, collaborative, and delivery-focused, offering an agile platform to prototype GenAI use cases, validate system architectures, and deploy advanced risk models.

about the job.

• Drive end-to-end delivery of AI/LLM risk projects, acting as the primary bridge between Risk business leadership, Data Science, and Cloud Engineering units.
• Evaluate incoming AI/LLM use cases across Risk domains, assessing technical feasibility, compute costs, ROI, and resource allocation.
• Lead discovery workshops to identify opportunities for process optimisation, automated risk monitoring, and workflow enhancement using GenAI and Machine Learning.
• Manage product backlogs, map user journeys, and write granular technical user stories with explicit acceptance criteria for engineering sprints.
• Oversee Proof-of-Concept (PoC) activities, validate model performance metrics, and consolidate assessment results for executive steering committees.
• Formulate business cases, define benefits realisation frameworks, and track KPIs to evaluate commercial impact.
• Partner with AI and data engineering teams to run prototype data queries in Python and SQL, ensuring data readiness and pipeline integrity.
• Document regulatory considerations, governance requirements, and audit trails necessary for enterprise AI adoption in risk platforms.
• Support project migration, testing, and deployment of risk analytics models across Cloud Platforms (AWS, Azure, or GCP).

skills & experience required.

• Minimum 8+ years of experience as a Business Analyst, Project Manager, or AI Product Manager within Financial Services, Insurance, or Risk Management.
• Demonstrated track record in Agile project management, backlog prioritization, user story creation, and cross-functional sprint delivery.
• Hands-on proficiency in Python and SQL for data exploration, prototyping, and analysis.
• Solid conceptual and practical understanding of Machine Learning (ML), LLMs / GenAI, and Data Science lifecycles.
• Practical understanding of Cloud Computing architectures (AWS, Azure, or GCP).
• Proven experience conducting PoC evaluations, process mapping, and executive stakeholder management.
• Bachelor's or Master's degree in Computer Science, Quantitative Finance, Data Science, or a related quantitative field.
• Excellent communication and stakeholder management skills in Cantonese and English are required.

education

Bachelor Degree