summary

hong kong
contract
full-time

job category
information technology

job details

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.

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

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business analyst – ai & advanced risk analytics.

job details

skills

qualifications

education

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the application process.

apply with randstad.

we'll give you a call.

getting you registered.

compliance check.

reference and background check.

the perfect job for you.

the interview.

start your new job.

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