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AXA

Global insurer offering life, property, casualty

Data Science Analyst

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeHong KongNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, Statistics, or a related discipline is required.
  • Two to three years of professional experience in AI engineering, software engineering, machine learning, data science, data engineering, or related technical disciplines is required.
  • Hands-on experience developing, implementing, and deploying AI-powered applications or solutions is required.
  • Experience working with Large Language Models, Generative AI technologies, intelligent agents, or related AI solution development is required.
  • Proficiency in Python and modern software development practices is required.
  • Hands-on experience with Generative AI frameworks and AI orchestration platforms, such as LangChain or Microsoft Agent Framework, is required.
  • Understanding of Retrieval-Augmented Generation, prompt engineering, vector databases, and AI evaluation techniques is required.
  • Experience integrating AI services and APIs into enterprise applications is required.
  • Familiarity with Azure AI Services, Azure OpenAI, Databricks, or similar cloud-based AI platforms is required.
  • Understanding of AI solution architecture, deployment, monitoring, and lifecycle management is required.
  • Practical experience in data engineering concepts, including ETL/ELT processes, data modelling, SQL, and data pipeline development is required.
  • Experience with Git, CI/CD pipelines, and software deployment practices is required.
  • Practical experience using AI-assisted development tools such as GitHub Copilot or equivalent technologies is required.
  • Strong analytical and problem-solving skills are required.
  • Excellent communication and stakeholder management skills are required.
  • The candidate must be self-motivated, curious, and passionate about emerging AI technologies.
  • The candidate must be able to work effectively in a fast-paced and collaborative environment.
  • The candidate must have strong learning agility and willingness to experiment with new technologies.

Responsibilities

  • Design, develop, test, and deploy AI-powered applications leveraging Generative AI, Large Language Models, and intelligent agent technologies.
  • Build and maintain enterprise AI solutions such as knowledge assistants, document intelligence platforms, conversational AI systems, and workflow automation tools.
  • Develop Retrieval-Augmented Generation solutions using enterprise knowledge repositories, vector databases, and modern AI frameworks.
  • Design, evaluate, and optimize prompts, agent workflows, and orchestration logic to improve AI performance, reliability, and user experience.
  • Integrate AI services, APIs, and enterprise platforms to enable seamless adoption of AI capabilities across business functions.
  • Collaborate with business stakeholders, technology teams, and data teams to understand requirements and translate them into scalable AI solutions.
  • Support the end-to-end AI solution lifecycle, including evaluation, testing, monitoring, performance optimization, and governance.
  • Apply modern software engineering practices, including source control, testing, CI/CD, and DevOps principles, to develop production-ready AI applications.
  • Maintain and enhance existing data pipelines, data assets, and analytics solutions to support business operations, reporting requirements, advanced analytics, and AI applications, ensuring reliability, scalability, and data quality.
  • Work closely with stakeholders to support AI and data-related BAU activities while driving continuous improvement and automation opportunities.
  • Utilize AI-assisted development tools such as GitHub Copilot and similar technologies to improve development efficiency and innovation.
  • Document technical designs, implementation approaches, and operational procedures to support maintainability and knowledge sharing.
  • Stay current on emerging AI technologies, industry trends, and best practices, continuously contributing ideas and improvements to the team.

Desired Qualifications

  • Experience in data science, machine learning, predictive analytics, advanced analytics, or statistical modelling projects is advantageous.
  • Knowledge of AI governance, Responsible AI practices, model risk management, or AI compliance considerations is advantageous.
  • Experience in insurance, financial services, or other regulated industries is advantageous.
  • Familiarity with deep learning frameworks such as TensorFlow or PyTorch is advantageous.
  • Proficiency in Cantonese and Mandarin is advantageous.

About the Company

AXA

Global insurer offering life, property, casualty

AXA is a global insurer and asset manager that provides life, health, and property and casualty insurance, as well as related financial services. Its products work by customers paying insurance premiums in exchange for coverage against risks; AXA pools risk across many policyholders, prices premiums based on risk, and pays claims when events occur, while also offering investment and retirement products through its asset management arm. The company has grown through large acquisitions, giving it a wide geographic footprint and a diverse mix of personal, commercial, and specialty insurance offerings. This scale and breadth set AXA apart from many competitors, alongside a long history of strategic mergers that expanded its reach to customers around the world. AXA’s goal is to be a leading global insurer and asset manager, delivering financial protection and long-term value to customers and stakeholders.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1816

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