Bei Shan Tang Foundation is a private philanthropic foundation founded in 1985 to enhance global understanding of Chinese culture through traditional art and art history. Alongside this mission, since 2014 we have committed significant resources to transforming education in Hong Kong through Positive Education — cultivating resilience, inspiration, and collaborative communities grounded in evidence-based practices.
We empower students to embrace change, thrive, and lead purpose-driven lives. Through collaborations with schools and esteemed institutions locally and worldwide, we introduce pedagogical innovations and effective strategies for educators. We also provide scholarships for students with financial needs to pursue studies abroad, nurturing Hong Kong’s next generation of leaders.
The role
Reporting to the Director (Education), you will serve as the Foundation’s quantitative expert — ensuring our education initiatives are grounded in rigorous evidence and our impact is clearly understood. You will own the full data cycle: from designing measurement approaches and managing longitudinal datasets through statistical analysis, interpretation, and translating findings into clear insights for diverse audiences. While you will work independently on technical analyses, you will collaborate closely with colleagues to ensure every analysis addresses meaningful questions that matter for students, educators, and the Foundation’s mission.
Key responsibilities
Measurement and insight generation
- Design for understanding: Translate research and evaluation questions into appropriate quantitative measurement frameworks, adapting or developing tools that capture what matters in education and wellbeing initiatives.
- Build the evidence base: Establish, maintain, and manage multi-wave and longitudinal datasets from the Foundation’s research, evaluation, and education programs, ensuring data quality and accessibility.
- Analyze with rigor: Select and apply appropriate statistical methods — including descriptive statistics, psychometric analysis, group comparisons, regression, and longitudinal modeling — based on research questions, measurement characteristics, and data structure.
- Uncover what matters: Identify meaningful patterns, trends, and findings that support continuous improvement of the Foundation’s education and wellbeing programs.
Communication and impact
- Translate complexity: Prepare clear summaries of analytical findings across multiple formats — spreadsheets, tables, infographics, and written reports — ensuring technical accuracy without sacrificing accessibility.
- Bridge worlds: Interpret statistical findings and communicate their implications and limitations clearly to non-technical colleagues, helping them make informed decisions.
- Share learning: Contribute to deliverables that promote public awareness and engagement, including presentations, reports, and academic papers that advance the field.
You may also contribute to knowledge management within the Foundation and assist in facilitating education-related professional development offerings.
Who you are
We value how you approach your work as much as what you know. The strongest candidates will recognize themselves in the following:
- You believe data is a tool for positive change, not an end in itself. You are driven by curiosity about what helps students thrive and educators succeed.
- You balance rigor with pragmatism. You apply sophisticated methods when they add value, but you also know when a simpler approach tells the story more clearly.
- You are a careful listener and clear communicator. You ask questions to understand what colleagues truly need, and you explain complex findings in ways that empower rather than confuse.
- You are systematic and detail-oriented, but you never lose sight of the bigger picture — the students and educators whose lives our programs touch.
- You are intellectually honest. You report findings accurately, acknowledge limitations openly, and view unexpected results as opportunities to learn.
- You are deeply curious about Hong Kong’s education system and genuinely motivated to contribute to its improvement.
What you’ll bring
- A bachelor’s degree in Statistics, Data Science, Psychology, Education, Social Sciences, or a related quantitative discipline (postgraduate qualification preferred).
- 2–5 years of experience in data analysis, quantitative research, program evaluation, or educational/social research, with a track record of independently conducting rigorous analyses.
- Strong proficiency in SPSS, R, or Python, with demonstrated ability to conduct descriptive statistics, psychometric analysis, group comparisons, regression, and longitudinal or repeatedmeasures analyses.
- Solid understanding of research methodology, quantitative analysis, and measurement principles. Experience with multi-wave or longitudinal datasets is an advantage.
- Exceptional attention to detail and systematic approach to data quality, statistical analysis, and interpretation.
- Experience in data visualization and workflow automation is a strong asset.
- Proficiency in English and Chinese; ability to work collaboratively in a multidisciplinary team.
Terms and benefits
This is a one-year fixed-term contract, renewable based on mutual agreement and operational needs. We offer competitive remuneration commensurate with experience, a 5-day work week, compensatory leave for weekend work, compassionate leave, comprehensive medical and dental insurance, and annual health checkups.
How to apply
Bei Shan Tang Foundation is an equal opportunity employer and welcomes applications from all qualified candidates. Fresh graduates with relevant skills are encouraged to apply; experience in education and psychology is an advantage.
To apply, please submit your CV and a brief cover letter indicating your earliest starting date and expected salary to Ms. Erica Yam (Senior Programme Manager) at ericayam@beishantang.org with “Application for Data Analyst (Measurement, Evaluation and Learning)” in the subject line.
Applications will be reviewed on a rolling basis until the position is filled. Only shortlisted candidates will be contacted.
