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  "job_description": "Lead Analyst\n\nLondon (Hybrid)\n\nUp to £70,000\n\nThis is a great Lead Analyst opportunity for someone who wants ownership, visibility, and the chance to shape how analytics is delivered, not just maintain dashboards. You will be joining a growing function that is investing heavily in data transformation. There is real scope to influence strategy, improve reporting capability, and develop a team, while partnering closely with international recruitment and marketing stakeholders.\n\nThe Company:\n\nA global education organisation supporting international students into university study across multiple destinations. They operate across recruitment, pathway programmes and wider student support services.\n\nThe Role:\n\nThis is a Lead Analyst role with a strong commercial lens. You will sit across recruitment and marketing, acting as the bridge between reporting, engineering and business stakeholders.\n\nYou will be responsible for:\n• Delivering pipeline, conversion and agent performance analysis\n• Owning BAU reporting and early stage forecasting\n• Improving and repurposing existing dashboards and analytics products\n• Translating stakeholder needs into clear specifications for data engineering and IT\n• Prioritising workload and managing expectations confidently\n• Coaching analysts and building team capability\n• Supporting a major data transformation programme including Microsoft Fabric, lakehouse architecture and Power BI\n• Leading reporting migration, validation and quality assurance\n• Contributing to early forecasting models, with longer term exposure to data science projects\n\nWhat They Are Looking For:\n• Strong experience in analytics or BI roles with clear commercial exposure\n• End to end delivery of reporting or analytics projects\n• Confidence influencing senior stakeholders\n• Experience mentoring or managing junior analysts\n• Solid Power BI and SQL background, Fabric exposure is beneficial but not essential\n• Strong experience building data models end to end, and working in DAX",
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  "job_posted_at_timestamp": 1773360000,
  "job_posted_at_datetime_utc": "2026-03-13T00:00:00.000Z"
}