Hire Data Analyst for Universities
Senior, direct, no layers

A data analyst turns the data a university already collects into decisions: which programmes attract enquiries that convert, where applications stall, where students disengage, and what deserves attention this term. For universities and higher-education institutions, data is usually plentiful and unusable: exports from several systems, definitions that differ by team, and reports nobody trusts. The work starts by agreeing what each number means, then builds dashboards that answer specific questions, not dashboards that display everything.

Engagements start with a conversation about the actual job to be done, not a package. Book a free discovery call and we will test the fit before any scope is agreed.

Universities typically run a student information system such as Ellucian Banner, Workday Student, or PeopleSoft Campus Solutions, a learning platform such as Canvas, Moodle, or Blackboard Learn, and a recruitment CRM such as Slate or Salesforce Education Cloud, with lecture capture and video through Panopto or Zoom. These systems are owned by different teams, change on different cycles, and rarely agree on what counts as a single student record. Work that ignores that reality gets stuck in procurement and integration review, so the practical approach is to integrate with the system of record for each job and to keep academic, admissions, and finance data in their proper homes. Analysis is built from your existing systems and analytics tools, with definitions documented alongside every dashboard, so figures can be checked back to source rather than taken on trust.

The practical rule is simple: new work should reduce the number of places staff have to look, not add another one. That is why integration, permissions, and handover are part of the scope from the start, rather than items discovered after launch.

The realistic outcome is fewer arguments about numbers and faster decisions about intakes, support, and programme focus. Analysis does not manufacture insight from bad data: where data is incomplete, the report says so and shows what to record better next term. Over time, the organisation stops re-litigating definitions and starts acting on the same picture.