HDSSZ_Data Scientist, AI COE

Position Description

Data Scientist, AI COE is responsible for building and maintaining statistic models, technical algorithms, and deploying AI-powered solutions to automate and augment HAECO’s business processes. He/She will be working closely with all HAECO business units and collaboratively across Group Digital & Technology and IT, to deliver end-to-end solutions.

What You'll Do

• Build statistical models, technical algorithms to generate different forecasting and simulation results to ensure the availability of actionable insights to support business decisions, process improvement and customer satisfaction
• Monitor data statistical models and tools
• Design, develop, and deploy AI-powered internal solutions — predominantly AI agents, and, where applicable, retrieval / RAG applications, document-intelligence pipelines, or machine-learning components.
• Work closely with business analysts and business stakeholders to translate business requirements into well-scoped use cases, including success metrics, data requirements, and go / no-go criteria.
• Conduct AI solution development feasibility study for business by performing data analysis and evaluating AI adoption readiness.
• Maintain the central repository of agents and deployed models.
• Uphold the non-functional quality and responsible-AI practice of AI solutions including robust evaluation, monitoring, and guardrail systems aligned with HAECO policy.

What You'll Need

1.Functional and other Relevant Experience

• Minimum 3 years working experience in AI, machine learning and statistical roles
• Proven track record of implementing big data projects
• Solid understanding and experience in using statistical models and machine learning algorithms such as Forecasting, Classification, Clustering, and Optimization algorithms is an advantage
• Demonstrated hands-on experience in the development of at least one machine learning or LLM-powered application or AI agent, whether in production or in pilot, encompassing prompt and context engineering, retrieval and RAG
• Ability to translate business workflows into effective digital, AI-enabled solutions through close collaboration with digital, IT, and business teams
• Hands-on experience with at least one LLM or agent framework — for example, Azure AI Foundry, Model Context Protocol (MCP) etc.
• Technical Expertise in core analytic methods such as predictive modelling, simulation, customer segmentation /clustering, etc. is an advantageA proven record of operating within cross-functional teams — including business analysts, system developers, data engineers, and software engineers

2.Leadership Competencies

• Collaborating & Influencing: Engage internal and external stakeholders at HAECO to help business units understand the statistical models, technical algorithms, AI agent capabilities, agentic workflows, and the potential opportunities for process automations and augmentation.
• Business Acumen: Stay current with latest data analytics and agentic AI technologies to identify opportunities for business process automation; translate business context into well-designed AI solutions. 
• Customer Focus: Proactively identify the needs and concerns of business stakeholders and reflect them into the AI solution delivery backlog and design decisions. 
• Drive for Result: Identify best data analytics technology and development of best practice for statistical models and apply best-fit AI technologies and frameworks, to deliver high-quality AI solutions.
• Continuous Improvement & Innovation: Passionate and self-motivated to learn emerging AI capabilities (e.g., agentic AI, multi-agent orchestration); continuously evaluate new tools, frameworks, and methodologies to improve solution quality and delivery speed.
• Developing Self/Others: Conduct regular peer code and design reviews;  share AI knowledge with cross-functional team members to build collective capability across the AI CoE.

3.Qualifications and other Relevant Knowledge

• Bachelor’s or Master’s degree holder in Engineering, Computer Science, Data Science, Information Systems, Software Engineering, Statistics, Mathematics, or a related field. 
• Strong knowledge in using cloud services from Azure Synapse Analytics and/or others is an advantage.
• Minimum 3 years of experience in digital adoption and familiarity with mainstream AI tools.
• Familiarity with AI-assisted coding tools (e.g., GitHub Copilot) and awareness of the verification and assurance challenges associated with AI-generated code is advantageous.
• Experience with model / agent registry and repository tooling (for example, MLflow or the Azure AI Foundry model catalogue) is advantageous.
• With Microsoft Azure Data Analytics, Azure AI, PowerBI certifications or equivalent certificationson other platforms (for examples, AWS, Databricks, or OpenAI) are advantageous.
• Fluent in English and Chinese is required.