Job Description

Senior Project Manager - Investments Data & Analytics

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6-Months

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Day Rate: $1050 - $1200

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Melbourne or Sydney

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Opportunity

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- An opportunity has become available for an experienced Project Manager to join the Investments Data & Analytics function within one of Australia's leading financial services organisations.
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- Working across a high-profile portfolio of investment technology initiatives, you'll lead the delivery of strategic data and platform projects that support investment operations, risk analytics and front-office decision making.
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- The ideal candidate will have a strong understanding of investment management, data platforms and Agile project delivery, with the ability to confidently engage senior stakeholders across both business and technology.
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Key Responsibilities

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- Lead the end-to-end delivery of complex Investment Data and Analytics projects.
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- Develop and manage project plans, milestones, budgets, RAID logs and governance artefacts.
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- Partner with Investment business stakeholders to define scope, priorities and delivery outcomes.
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- Coordinate cross-functional teams including Business Analysts, Data Engineers, Architects, Developers and QA.
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- Manage dependencies across multiple workstreams and delivery teams.
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- Drive Agile ceremonies including sprint planning, backlog refinement, showcases and retrospectives alongside Product Owners and Scrum teams.
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- Identify and manage project risks, issues and delivery dependencies.
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Experience

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- Project Management experience within Investment Management, Asset Management, Superannuation or Wealth Management.
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- Solid understanding of investment operations and investment data.
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- Experience delivering projects involving investment platforms, performance data, risk analytics or portfolio reporting.
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- Experience working with Agile delivery methodologies.
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- Strong knowledge of Jira, Confluence and Agile delivery frameworks.
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Highly Desirable

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- Private Markets (Infrastructure, Property, Private Equity, Credit)
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- Fund structures and investment operating models
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- Risk Analytics platforms; FactSet, Bloomberg, Aladdin, SimCorp or similar investment platforms
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- SQL or data analysis exposure (not hands-on, but sufficient to engage technical teams effectively)
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