Research Analyst (Statistics)
Research Analyst (Statistics)
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Job Description
Employment Type: 6-month fixed term Full Time or Part Time
Remuneration: $103866 - $110801 Full Time Equivalent 17% superannuation
Location: Kensington UNSW Campus (hybrid)
Why Your Role Matters
This role is a 6-month funded contract working within the Educational Data & Insights team at UNSW. Youll support the university by analysing student experience and education data helping leaders make informed evidence-based decisions that improve teaching and learning.
Youll play an important part in:
Collecting and analysing data from student surveys (QILT) to identify key trends and insights about student feedback
Preparing clear reports to help university staff understand what students are saying and how different groups of students are represented in the feedback
Performing statistical analysessuch as segmentation driver analysis SEM and hierarchical linear modellingto group students identify feedback drivers and examine relationships between indicators uncovering what matters most to them
Reviewing written qualitative feedback to find common themes and pinpoint where UNSW can improve
Helping develop ways to summarise students comments using Generative AI tools ensuring these are used thoughtfully and ethically
Working closely with your team and responding flexibly to the tasks and guidance set by the Manager Educational Data & Insights
This position does not have any direct management responsibilities. Your main goal will be to turn complex student feedback into clear actionable insights that help UNSW enhance the student experience.
Who You Are
We are looking for someone who is aligned with UNSWs vision and values able to communicate findings to relevant audiences and who comes with:
Confidence in statistical methods and analysis
Previous experience manipulating complex large datasets and translating them into meaningful insights
Ability to analyse and validate datasets using statistical techniques identifying patterns and relationships to support data-driven insights
Experience applying various research methods alongside data management and quality control
Fluency in R or in another modern data-science language such as Python
Relevant tertiary qualification and experience in Statistics Data Science Business Psychology Education Social Sciences or a related field could be relevant
Working hours are flexible although funded fulltime parttime arrangements are welcome. Please specify your availability and preference in your application. This is a hybrid role operated during business hours not fully remote and no weekend or evening work.
Candidates will need to have ongoing working rights this role is not available for sponsorship.
Benefits and Culture:People are at the core of everything we do. We recognise it is the contributions of our staff who make UNSW one of the best universities in Australia and the world. Our benefits include:
Access to up to 17% Superannuation contributions and additional leave loading payments
Additional 3 days of leave over the end of the year period
Discounts and entitlements (retail education fitness)
Recruitment process: Please submit your resume as well as cover letter that addresses your interest and skills and experience that you believe would make you successful. You will also be asked a couple of additional questions about your experience when applying.
Applications close:12 August 7PM. We reserve the right to close the application earlier.
Applications cannot be accepted if sent directly to the contact listed
UNSW is committed to equity diversity and inclusion. Applications from women people of culturally and linguistically diverse backgrounds those living with disabilities members of the LGBTIQ community; and people of Aboriginal and Torres Strait Islander descent are encouraged. UNSW provides workplace adjustments for people with disability and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.
Required Experience:
IC
Employment Type
Full-Time
