Specialist Data Analyst - Global Renewals at IFS1

About the role   IFS is looking for a Specialist Data Analyst to join the Global Renewals function and play a central role in the intelligence that drives customer retention, revenue growth, and strategic decision-making. This is a hands-on role at the intersection of analytics, operations, and innovation — building advanced reporting, transforming complex multi-source data, and working with global teams to deliver insights that make a measurable difference. You will own the full data lifecycle for renewals analytics: sourcing and transforming data, maintaining core operational datasets, building and publishing Power BI dashboards, and — critically — independently deriving the business intelligence that your stakeholders need. You will work closely with Renewals leadership, regional managers, and cross-functional partners across Finance, BI, and Sales Operations. This role suits someone who already works with AI tools as a natural part of how they think through analytical problems, design reporting structures, and raise the quality of their outputs. We are an AI-first business and we expect this role to reflect that — not as an aspiration, but as a current working practice. If you bring strong analytical rigour, deep technical capability, genuine business acumen, and the independence to run your own workload without close supervision — we want to hear from you.   What you will do   Data strategy and insight • Build and maintain advanced Excel workbooks for in-depth contract renewal calculations, forecasting, and dataset collation — supporting better workflows and more informed business decisions. • Develop and maintain dynamic Power BI dashboards and reports that deliver actionable insight aligned to IFS’s renewal and growth objectives, drawing on validated internal data sources. • Perform in-depth KPI analysis and scenario modelling to support quarterly and annual planning cycles, enabling data-driven decision-making across the business. • Track and report key metrics including renewal rate, ACV uplift, churn indicators, and ARR contribution — and proactively surface what the numbers mean, not just what they show. • Produce timely scheduled and ad hoc reports tailored to executive stakeholder needs, aligned to the business cadence and ready to use without further editing. • Continuously identify opportunities to improve data accuracy, quality, and relevance before issues reach stakeholders.  Operational intelligence • Source, cleanse, and unify data from diverse internal systems into consolidated datasets that provide a reliable, single view of the customer. • Track pricing trends, customer behaviour, and renewal patterns to uncover actionable intelligence that supports business performance. • Build and maintain operational performance tools that enhance visibility and support decision-making for leadership and regional managers. • Present data findings using clear visuals and concise narratives that drive alignment and action across business units.  Cross-functional collaboration • Partner with global teams across sales, renewals, and customer success to deliver data-driven insight that enhances customer engagement and revenue performance. • Develop data stories tailored to both technical and non-technical audiences, including executive leadership. • Support data literacy across the team by sharing knowledge of analytics tools, insight interpretation, and data-driven ways of working. • Contribute to cross-functional data-sharing initiatives that unlock incremental business value.  Automation and innovation • Automate recurring reporting and business processes using Power BI, Power Automate, and equivalent tools — reducing manual effort and increasing reliability. • Apply AI tools actively in your analytical workflow: to conceptualise approaches, sense-check logic, design reporting structures, and accelerate the quality of your outputs. • Explore AI and machine learning techniques to support predictive use cases including churn risk, renewal forecasting, and customer segmentation — as IFS continues to build its AI-first capability. • Continuously evaluate and adopt emerging tools and techniques that improve the efficiency and scale of analytics across the function.  What you bring   Renewals and revenue knowledge • Understanding of SaaS and enterprise software renewal mechanics — contract structures, uplift, ACV, ARR, and the nuances that affect how these are calculated and reported. • Working knowledge of churn risk indicators, renewal rate reporting, and the KPIs that drive performance conversations at a leadership level. • Ability to read a dataset and independently determine what it means for the business — identifying at-risk accounts, tracking performance against target, and interpreting anomalies without being directed to do so. • Consistent and independent application of business rules across reporting cycles, without requiring repeated clarification.  Technical capability • Advanced Excel: complex formula construction, multi-table modelling, named ranges, dynamic arrays, and structured workbook architecture built to be maintained by others. • Power Query: designing and maintaining multi-source transformation pipelines; hierarchy resolution logic; refresh and error handling; connectivity to enterprise source systems including ERP layers, analytical data stores, and cube-based reporting environments. • Power BI: end-to-end dashboard development from data model to published output, including DAX measures, workspace management, and delivery to executive audiences. • Data integrity: validating outputs, detecting structural changes in source data, reconciling discrepancies, and maintaining audit-ready datasets. • Enterprise data platform awareness: understanding how operational data flows from an ERP and adjacent systems through staging and analytical layers; ability to trace issues back to their origin.  Analytical and communication skills • Ability to translate a business question into an analytical approach and deliver a clear, defensible answer — not just a dataset. • Knowledge of BI visualisation best practice: structuring dashboards for executive consumption using KPI cards, trends, comparisons, and hierarchies. • Strong verbal and written communication — able to convey complex findings clearly to senior stakeholders and document work so that others can maintain it. • Experience adapting outputs for different audiences, from operational managers to executive leadership.  AI-assisted analytics • Active, working knowledge of AI tools (such as large language models) as part of the analytical workflow — to conceptualise report designs, sense-check data logic, draft business narratives, and explore approaches before building them. • Ability to frame a business intelligence problem clearly enough to get useful output from an AI tool, and to critically evaluate that output rather than accept it at face value. • Understanding of where AI accelerates analytical work and where human judgement and data expertise remain essential.