Closing on 28 Feb

Data Analyst

Knowledge and Advocacy Full-time - Permanent


We are growing our data analytics ability to maximise the use of our data from various sources, including online giving platform, web traffic and landscape surveys. We are also expanding our pool to include external databases. We know the power of data analytics to help us galvanise more to give of their time, talent and treasure and to empower those who are already giving to deepen and broaden their giving.

As part of the team, you will also be involved in quantitative research on volunteerism and philanthropy, and analysing data and trends on giving to inform and influence key stakeholders.

We seek motivated candidates with the passion to make NVPC a data-driven organisation, to carry out meaningful work at the intersection of non-profit, public and private sectors and to make a difference at national level.


  • Carry out end-to-end data analytics projects from business understanding, to data understanding, data preparation, modelling, evaluation and to deployment.
  • Involve in end-to-end quantitative research projects such as large scale landscape study of giving behaviour and attitudes among individuals and corporates.
  • Conduct secondary research and literature reviews on volunteerism and philanthropy.
  • Support collaborative data analytics and research work with partners such as government agencies, institute of higher learning.
  • Derive key insights and recommendations on how to galvanise more individuals and corporates to give of their time, talent and treasure and to empower those who are already giving to deepen and broaden their giving.
  • Communicate insights and recommendations via written or verbal presentations to key stakeholders, including internal stakeholders in NVPC and external stakeholders such as government agencies, companies, non-profits and funders, for application and advocacy.


  • Degree in Business Analytics, Computer Science, Statistics, Mathematics or other related field.
  • At least 1 year of experience in a data analytics or related role.
  • Proficient in data mining process such as CRISP-DM and data analytics techniques, including supervised learning (e.g. logistic regression, support vector machine, text mining) and un-supervised learning (e.g. clustering).
  • Proficient in research methods and process and statistical analysis
  • Proficient in statistical and analytics tools such as R and SPSS and business intelligence tool such as Tableau.
  • Proficient in SQL.
  • Strong written skills in English.
  • Good interpersonal and communication skills.
  • Curiosity and interest in looking for data and statistics that creates value.

Interested applicants are invited to send your updated resume via Jobstreet, LinkedIn or [email protected] We regret that only shortlisted applicants will be notified.