United Kingdom
15 hours ago
Lead Specialist, Data Analytics & Business Intelligence

Context 

Pearson’s commitment to learning extends to every aspect of our business — including how we invest in our future. With a wealth of data at our fingertips, we have an exciting opportunity to further elevate our decision-making. In this role, you will play a key part in unlocking new insights from our data, shaping more effective investment strategies, and helping both Pearson and grow and adapt in a dynamic environment. 

This role supports Pearson’s global business by strengthening performance, content-related, and financial analytics, helping improve visibility, measurement, and decision-making across investment, delivery, and outcomes. 

We are looking for a hands-on data and analytics specialist who can help Pearson better leverage its data assets, improve forecasting and insight generation, and contribute to the continued scaling of analytics capabilities across the organisation. 

The role will help build a cross-integrated view of data that is currently fragmented or under-utilised, enabling more informed, data-driven decisions. It requires a strong analytical background, curiosity, and the ability to engage, challenge, and influence credibly across a complex enterprise environment. 

 

Key Responsibilities 

Performance, Content & Financial Analytics 

Develop dashboards and reporting that provide insight into investment performance, content-related activity, and financial outcomes. 

Support analysis across budgets, forecasts, actuals, and performance trends. 

Enable consistent, multi-dimensional views (e.g. organisational, regional, functional) to support decision-making. 

 

Data Integration, Quality & Automation 

Work with data from multiple enterprise systems and cloud-based platforms. 

Contribute to the integration, transformation, and curation of datasets used for reporting and analysis. 

Reduce manual reporting through standardised datasets, dashboards, and light-touch automation. 

 

Advanced & AI-Assisted Analytics 

Apply analytical techniques to identify patterns, variances, and opportunities across performance and financial data. 

Support the use of AI-assisted analytics to improve insight generation, variance explanations, and reporting efficiency. 

Operate within established data governance, security, and tooling standards. 

 

Stakeholder Engagement & Delivery 

Partner with stakeholders to translate analytical needs into clear, decision-ready outputs. 

Manage priorities across multiple requests and timelines. 

Communicate insights clearly to both technical and non-technical audiences. 

 

Skills & Experience 

Core Analytics & Business Skills 

Strong experience in data analytics, reporting, and performance analysis 

Solid business acumen and financial literacy, with confidence working across budgets, forecasts, and actuals 

Ability to synthesise complex data into clear, actionable insights 

Experience contributing to, or supporting, large and complex analytical initiatives 

 

Data & Technology 

Strong capability in SQL; KQL experience an advantage 

Proficiency in enterprise visualisation tools, such as Tableau and/or Power BI 

Experience with data preparation and analytics tools (e.g. Alteryx, KNIME, Excel); Python and/or R an advantage 

Experience working with enterprise-scale systems, such as Oracle (e.g. EBS / Fusion / OPA) and other operational platforms (e.g. Salesforce or similar) 

Understanding of cloud data platforms, including GCP, with exposure to Azure and/or AWS 

Comfortable working with large, complex datasets in a governed enterprise environment 

Exposure to group reporting or consolidation systems (Oracle / Hyperion advantageous) 

Familiarity with light automation using tools such as Power Automate is a plus 

 

Ways of Working  

Delivery-focused, pragmatic, and comfortable navigating ambiguity 

Confident operating in matrixed, multi-stakeholder environments 

Strong written, verbal, and presentation communication skills, including executive-level reporting 

 

Qualifications 

Degree-level education in a numerate or analytical discipline 

Master’s degree or equivalent experience an advantage 

ACA, ACCA, CIMA or equivalent accounting qualification preferred.

 

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