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Data Analyst

SMAN 90 Jakarta

Remote ・ パートタイム

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Applicants should have a bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Education, or a related discipline, or equivalent practical experience. Candidates with experience in educational or academic data are welcome, though this is not mandatory. The role is suited to…
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仕事内容

Role overview

SMAN 90 Jakarta is hiring a part-time, remote Data Analyst to support its academic and operational reporting needs. In this position, you will work with data from internal systems and spreadsheets, turning raw information into useful insights for school leadership and staff.

Core work

You will be responsible for gathering, cleaning, and organizing data, then examining it to identify trends in student performance, attendance, and other school-related measures. The role also involves building reports, dashboards, and visual presentations that make complex findings easy to understand and use.

Collaboration and improvement

Beyond analysis, you will coordinate with stakeholders to clarify data needs, strengthen data quality practices, and suggest practical improvements backed by evidence for school programs and initiatives.

Qualifications

  • Strong analytical ability and experience working with data to interpret complex information and produce meaningful conclusions.
  • Working knowledge of statistics and quantitative techniques to support analysis, reporting, and recommendations.
  • Experience structuring datasets or databases for effective analysis and reporting.
  • Clear communication skills with the ability to present findings to non-technical audiences.
  • Comfort using spreadsheet software such as Excel or Google Sheets; familiarity with visualization tools such as Tableau, Power BI, or similar tools is an added advantage.
  • Basic knowledge of SQL, Python, R, or similar query/programming languages is helpful.
  • Ability to work independently in a remote setup, manage time well, juggle multiple tasks, and maintain attention to detail.
  • A bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Education, or a related area, or equivalent hands-on experience.
  • Experience handling educational or academic data is preferred but not mandatory.

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