Prospect Intelligence Analyst - Flexible Work

James Cook University; Townsville City; Presencial; AUD 91.000 - 98.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Generous superannuation up to 17%

5 weeks annual recreation leave

6 months paid parental leave

Flexible working options

On-site childcare and medical services

Staff study assistance and paid study

Descripción de la vacante

James Cook University seeks a Prospect Intelligence Analyst to provide research, intelligence profiles and briefing materials to support philanthropic fundraising and stakeholder engagement. You will manage prospect analysis, due diligence, and reporting while leveraging CRM systems and advanced analytics to strengthen fundraising efforts.

You will collaborate with the Advancement team to enhance systems and workflows, delivering timely insights and data-driven recommendations across multiple

Formación

• Curious and analytical, able to research, assess and interpret information from multiple sources.
• Experience with databases, CRM systems and reporting tools; ensure data integrity and confidentiality.
• Strong written and verbal communication and ability to provide clear recommendations and briefings.

Responsabilidades

• Deliver high‑quality research, intelligence profiles and briefing materials for philanthropic fundraising.
• Support prospect management through portfolio analysis, due diligence, tracking, and pipeline reporting.
• Produce reports, dashboards and analytical insights to inform fundraising planning and engagement.

Descripción del empleo

James Cook University seeks a Prospect Intelligence Analyst to provide research, intelligence profiles and briefing materials to support philanthropic fundraising and stakeholder engagement. You will manage prospect analysis, due diligence, and reporting while leveraging CRM systems and advanced analytics to strengthen fundraising efforts.

You will collaborate with the Advancement team to enhance systems and workflows, delivering timely insights and data-driven recommendations across multiple