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Executive Trainee

The University of Hong Kong

Apply now Ref.: 534895
Work type: Full-time
Department: Development & Alumni Affairs Office (60800)
Categories: Executive / Technical / Support
Hong Kong

The Development & Alumni Affairs Office is establishing a new AI & Data Lab to support innovation in advancement intelligence. We are looking for a motivated and curious Executive Trainee to join our team. This is a 2-year structured program designed to develop your skills in data analytics, business intelligence, and data management within a higher education advancement setting. You will work closely with experienced analysts to transform alumni and donation-related data into actionable insights, supporting fundraising strategies and enhancing alumni engagement.

 

Key Responsibilities
Under guidance and supervision, the Trainee will:

  • Assist in the development and maintenance of reports, dashboards, and data visualizations to support decision-making by senior leadership;
  • Support data analysis to uncover trends, patterns, and opportunities that drive fundraising and alumni engagement;
  • Help maintain data quality and integrity by assisting with data cleansing, validation, and documentation tasks;
  • Participate in the design and preparation of datasets for potential machine learning models in advancement activities;
  • Collaborate with team members to understand business needs and contribute to analytical solutions;
  • Learn and apply data governance and compliance practices across systems and workflows; and
  • Contribute ideas and observations to support the continuous improvement of the Lab's data strategy and roadmap.

 

Requirements

  • Bachelor's degree or above in Artificial Intelligence, Data Science, Statistics, Computer Science, Information Systems, Mathematics, Engineering, Quantitative Finance, or a related quantitative field
  • Proficiency in or strong willingness to learn AI tools and technologies to enhance work efficiency and drive data-driven innovation
  • Fresh graduates or candidates with 1–2 years of work experience are welcome to apply
  • Basic proficiency in or strong willingness to learn SQL and Python for data analysis
  • Familiarity with or interest in learning data visualization platforms (e.g., Power BI, Tableau, Qlik) is an advantage
  • Strong analytical and problem-solving skills with high attention to detail
  • Ability to work with structured datasets and ensure data accuracy
  • Good communication skills and ability to present findings clearly to team members
  • A proactive attitude, eagerness to learn, and ability to work both independently and collaboratively
  • No prior experience in fundraising or alumni relations is required—we welcome candidates from various backgrounds who are passionate about using data for positive impact

 

What We Offer

  • Structured 2-Year Program: A dedicated training program to build a strong foundation in data analytics within a real-world setting.
  • Mentorship: Direct guidance from senior data professionals in the newly established Data & AI Lab.
  • Skill Development: Hands-on training in SQL, Python, Power BI, and data governance best practices.
  • Real-World Impact: Opportunity to work with real alumni and fundraising data that directly supports the University's mission.
  • Career Progression Opportunity: High-performing trainees may be considered for a regular position upon successful completion of the 2-year program.

 

Appointment Details

The appointment will be made on a fixed-term full-time contract for 2 years, to commence as soon as possible with the possibility of renewal subject to satisfactory performance.  A highly competitive salary commensurate with qualifications and experience will be offered, together with contract-end gratuity and University contribution to a retirement benefits scheme at 10% of basic salary.  Other benefits include annual leave and medical benefits.

 

How to Apply

Those interested in the post may contact Ms. Ronnie Lee of the Development & Alumni Affairs Office (ronnilee@hku.hk) for further information.

The University only accepts online applications for the above post. Applicants should apply online and upload an up-to-date C.V.  Review of applications will commence as soon as possible and continue until April 22, 2026 or until the post is filled, whichever is earlier.  

 

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