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Data Scientist/ Data Analyst

External
NATIONAL UNIVERSITY OF SINGAPORE logoNational University Of Singapore · Lower Kent Ridge Road, Singapore
S$54K–S$91K/yrFull-timeUnknown1w ago
Information Technology
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Requirements

  • Successful candidate should have the following qualifications and capabilities:
  • Bachelor degree in Data Analytics, Applied Statistics or Mathematics, Computer Science or another quantitative field, but higher qualifications (Master's or PhD) is preferred.
  • Excellent knowledge of at least one of the following scripting/programming languages: Python, R, Java, C++, C#.Net, SQL.
  • Proficiency in using Business Intelligence tools (e.g. Power BI, Tableau or Qlik Sense)
  • Experience in applying machine learning techniques and designing algorithms that are scalable and production-grade.
  • Knowledge of database, ETL and data API concepts.
  • Strong analytical, problem-solving skills and critical thinking with the ability to articulate ideas with data.
  • Excellent written and verbal communication skills for coordinating across teams.

Additional Information

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Data-Scientist-Data-Analyst/30525-en_GB/ We regret that only shortlisted candidates will be notified. Job Description To join the team at the Office of Data and Intelligence at the National University of Singapore (NUS) with the collection, analysis, visualization of data and presentation of analytical results for regular and ad-hoc reporting purposes to meet multiple information and strategic requirements for the various stakeholders of the university. The successful candidate will join a team of other data analysts and data scientists to engage in the following activities: Create detailed reports on data sources, methodology, analytical techniques, analytical results and insights for stakeholders. Develop visualisations and presentations for dissemination of analytical results and derivation of actionable insight. Assist other units in the university with enhancing their data culture and capabilities. Develop data repositories and system to enable key stakeholders to access regular reports.


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