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    <title>Jobs at University of Staffordshire | Business Intelligence and Management Reporting</title>
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          <title><![CDATA[Insight Analyst (BIMR65-26)]]></title>
          <link>https://jobs.staffs.ac.uk/rss/click.aspx?ref=BIMR65-26</link>
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            <p id="isPasted"><strong>About the Role</strong></p><p>Business Intelligence and Management Reporting (BIMR) supports strategic and operational decision making across the University of Staffordshire through the delivery of data and insight. Working collaboratively with schools and professional services, BIMR helps stakeholders understand performance, identify opportunities for enhancement, and make evidence-based decisions.</p><p>We are seeking an Insight Analyst to play a key role in strengthening the University&rsquo;s analytical capability and supporting a more insight-driven approach to decision-making. Working closely with the BI Business Partner, you will support schools and services in understanding performance against strategic objectives, translating complex data into meaningful insight and actionable recommendations.</p><p>The role will involve analysing internal and external datasets relating to recruitment, student experience and student outcomes, helping stakeholders identify trends, risks and opportunities. You will contribute to the development of self-service business intelligence, support the embedding of data-informed decision-making across the institution, by supporting colleagues to improve data literacy capability throughout the University.</p><p>This is an opportunity to work in a collaborative business partnering environment where insight and analytics directly support institutional strategy, performance improvement and student success.</p><p><strong>Main responsibilities</strong></p><ol start="1" type="1"><li>Support the provision of analysis and interpretation of internal and external data relating to recruitment, student experience and student outcomes.&nbsp;</li><li>Produce insight and recommendations relating to University performance against key performance indicators, supporting continuous enhancement across the institution.&nbsp;</li><li>Analyse complex datasets using a range of quantitative and qualitative methodologies to identify trends, risks and opportunities and inform strategic decision-making.&nbsp;</li><li>Support business partnering activity by interpreting and translating data and insight for stakeholders across schools and professional services, acting as a critical friend where appropriate.&nbsp;</li><li>Support the delivery of a hub-and-spoke approach to business intelligence and analytics, helping embed effective use of data and self-service reporting across the University.&nbsp;</li><li>Contribute to the development of data literacy and analytical capability across the institution.&nbsp;</li></ol><p><strong>About You</strong></p><p>You will have experience of analysing and interpreting complex datasets and presenting insight clearly to a range of audiences. You will be confident working with stakeholders, translating business requirements into analytical outputs and supporting evidence-based decision-making.</p><p>You will also bring:</p><ul type="disc"><li>Strong analytical and problem-solving skills</li><li>Experience working with large and complex datasets&nbsp;</li><li>Experience using BI tools such as Power BI&nbsp;</li><li>Excellent communication and stakeholder engagement skills&nbsp;</li><li>The ability to present technical information in an accessible and meaningful way</li></ul><p><strong>Further Information</strong></p><p>Please contact Scott Marsh on&nbsp;<a href="mailto:Scott.Marsh@Staffs.ac.uk">Scott.Marsh@Staffs.ac.uk</a>&nbsp;</p>
            <p>
              Closing Date: 12 Jun 2026<br />
            </p>
            <p>
              Department: Professional Support 
            </p>
            <p>Salary: &#163;33,482 to &#163;38,249 Per Annum Full Time Fixed Term for 12 Months</p>
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          <category><![CDATA[Professional Support ]]></category>
          <pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate>
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