Business Analyst – AI & Advanced Risk Analytics

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 700,000 - 1,000,000; Full time

Job summary

Randstad Hong Kong Limited seeks a skilled data science professional to bridge risk requirements with modern analytics. You will design, develop, and implement AI/ML-driven solutions to automate risk scoring, continuous vendor monitoring, and regulatory assessments within Hong Kong operations.

The role focuses on deploying ML models, integrating Generative AI, and building secure data pipelines across cloud environments, while ensuring governance and stakeholder communication in English.

Qualifications

• Bachelor Degree in Computer Science, Data Science, Statistics, Information Systems, Financial Engineering, or related quantitative discipline.
• Proficient in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
• Practical understanding of LLMs / GenAI frameworks (prompt engineering, RAG architectures, LangChain, API integrations).
• Hands-on experience with modern Cloud platforms (AWS, Azure, or GCP).
• Strong SQL skills and experience manipulating large-scale, unstructured datasets.
• Functional domain exposure to Operational Risk, Non-Financial Risk (NFR), Third-Party Risk Management (TPRM), or Compliance within Banking/Insurance/Financial Services (preferred).
• Ability to articulate complex data science and AI concepts to non-technical stakeholders.
• Language: Fluent in English; Cantonese or Mandarin an advantage.

Responsibilities

• Requirements & Solution Architecture: Elicit, evaluate, and translate business challenges into technical data science and AI-driven solutions.
• AI & LLM Implementation: Prototype and integrate Generative AI / LLMs to streamline contract review, vendor risk tiering, policy checks, and regulatory workflows.
• Predictive Modeling & Analytics: Develop and maintain ML and statistical models to identify vulnerabilities, concentration risks, and performance anomalies.
• Cloud & Data Pipelines: Build and optimize data ingestion pipelines and risk data marts across secure cloud environments.
• Documentation & Governance: Produce functional specs, data dictionaries, user stories, and model governance docs in line with AI governance guidelines.

Skills

Python

LLMs

Cloud platforms

SQL

Education

Bachelor Degree

Tools

Pandas

NumPy

Scikit-learn

PyTorch/TensorFlow

Job description

about the company.

Role SummarySitting within the wider Group Operational Risk function and supporting the Third Party & Outsourcing Risk team, this role bridges business risk requirements with modern technology. You will design, develop, and implement advanced analytics, Machine Learning (ML), and AI/LLM-driven solutions to automate risk scoring, continuous vendor monitoring, anomaly detection, and operational risk assessments across AIA Group’s operating units.

about the job.

• Requirements & Solution Architecture: Collaborate with Group Risk leaders to elicit, evaluate, and translate business challenges into technical data science and AI-driven solutions.
• AI & LLM Implementation: Assist in prototyping and integrating Generative AI / Large Language Models (LLMs) to streamline contract review, vendor risk tiering, policy compliance checks, and regulatory assessment workflows.
• Predictive Modeling & Analytics: Develop and maintain Machine Learning and statistical models using Python to identify emerging third-party operational vulnerabilities, concentration risks, and performance anomalies.
• Cloud & Data Pipelines: Work alongside enterprise architecture and IT to build and optimize data ingestion pipelines and risk data marts across secure cloud environments.
• Documentation & Governance: Produce functional specifications, data dictionaries, user stories, and model governance documentation in compliance with enterprise AI and model risk management guidelines.

Key Requirements

• Education: Degree in Computer Science, Data Science, Statistics, Information Systems, Financial Engineering, or a related quantitative discipline.
• Technical Proficiency:
• Proficient in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, etc.).
• Practical understanding of LLMs / GenAI frameworks (e.g., prompt engineering, RAG architectures, LangChain, API integrations).
• Hands-on experience with modern Cloud platforms (AWS, Azure, or GCP).
• Strong SQL skills and experience manipulating large-scale, unstructured datasets.
• Functional Domain: Prior exposure to Operational Risk, Non-Financial Risk (NFR), Third-Party Risk Management (TPRM), or Compliance within Banking, Insurance, or Financial Services is preferred.
• Communication: Ability to articulate complex data science and AI concepts clearly to non-technical business stakeholders.
• Language: Fluent in English (written and verbal); Cantonese or Mandarin is an advantage.

skills

no additional skills required

qualifications

no additional qualifications required

education

Bachelor Degree