About Pearson
Pearson is committed to a world that’s always learning and to the talented people who make it possible. From bringing lectures vividly to life to transforming textbooks into digital learning experiences, we continuously reimagine how people learn best—whether supporting one learner locally or entire education communities globally. We are bold thinkers and innovative problem-solvers who inspire each other to explore new frontiers in technology, analytics, and learning. By pushing the boundaries of innovation—and challenging ourselves to go further—we create meaningful solutions that empower learners, educators, and organizations around the world.
About the Role
We are seeking a highly skilled and strategic Data analytics Lead to lead advanced analytics, business intelligence, and AI-driven transformation initiatives within the RevOps Sales Intelligence organization. This role combines deep analytical expertise, business acumen, leadership, and emerging AI capabilities to transform complex data into actionable insights and scalable intelligent solutions that drive sales performance, operational excellence, and strategic decision-making. The ideal candidate is passionate about leveraging modern analytics platforms, automation, Generative AI, and data storytelling to improve business outcomes, enhance productivity, and accelerate innovation across the organization.
Key Responsibilities
Data Analytics & Business Intelligence
- Lead the design, development, and delivery of scalable analytics solutions, executive dashboards, KPIs, and operational reporting.
Translate complex business questions into analytical frameworks, actionable insights, and data-driven recommendations.
Partner with Sales, RevOps, Finance, Product, and Leadership stakeholders to identify opportunities for business optimization and growth.
Perform advanced data analysis using SQL, KQL, Python, Power BI, Microsoft Fabric, Databricks, or similar technologies.
Develop forecasting models, performance measurement frameworks, trend analysis, and business health metrics.
Ensure data quality, governance, consistency, and reporting accuracy across multiple enterprise systems.
Drive self-service analytics capabilities and data democratization initiatives.
Leadership & Collaboration.
Manage prioritization, roadmap planning, and execution across multiple analytics and AI initiatives.
Collaborate cross-functionally with Engineering, Data Science, Operations, Product, Finance, and Executive Leadership teams.
Present insights, recommendations, and strategic narratives effectively to both technical and non-technical audiences.
Foster a culture of innovation, experimentation, continuous learning, and operational excellence.
Data Platform & Technical Excellence
Work with modern cloud data platforms including Microsoft Azure, Databricks, SQL Server, Synapse, Microsoft Fabric, and related ecosystems.
Optimize data pipelines, semantic models, reporting performance, and enterprise BI architecture.
Contribute to analytics best practices, scalable data solutions, and long-term modernization initiatives.
AI Innovation & Automation
Identify and implement AI-driven opportunities that improve analytics efficiency, business insights, and operational productivity.
Leverage Generative AI, Copilot technologies, machine learning, and automation solutions to modernize reporting and workflow processes.
Partner with engineering and data science teams to operationalize scalable AI-powered analytics solutions.
Evaluate emerging AI technologies, analytics platforms, and industry trends to inform innovation strategy and roadmap planning.
Build proof-of-concepts (POCs) and scalable AI solutions that drive measurable business impact and user adoption.
Champion responsible AI practices, governance, compliance, security, and ethical data usage.
- Bachelor’s degree in Data Analytics, Computer Science, Statistics, Information Systems, Engineering, or a related field.
- 7+ years of experience in data analytics, business intelligence, or related analytical roles.
- Strong expertise in SQL, KQL, and at least one analytics/programming language such as Python or R.
- Proven experience with BI and visualization tools such as Power BI and Tableau, including AI-driven reporting capabilities.
- Experience working with cloud data platforms such as Azure, AWS, or GCP.
- Strong analytical thinking, problem-solving, and stakeholder management skills.
- Excellent communication, storytelling, and executive presentation abilities.
- Experience with Microsoft Fabric, Databricks, Copilot technologies, or machine learning platforms.
- Knowledge of Generative AI, LLM applications, prompt engineering, and AI automation workflows.
- Experience leading enterprise-scale analytics modernization or digital transformation initiatives.
- Familiarity with Agile methodologies and product operating models.
- Experience supporting Sales, Revenue Operations, or Commercial Intelligence organizations preferred.
Required Qualifications
- Bachelor’s degree in Data Analytics, Computer Science, Statistics, Information Systems, Engineering, or a related field.
- Proven years of experience in data analytics, business intelligence, or related analytical roles.
- Strong expertise in SQL, KQL, and at least one analytics/programming language such as Python or R.
- Proven experience with BI and visualization tools such as Power BI and Tableau, including AI-driven reporting capabilities.
- Experience working with cloud data platforms such as Azure, AWS, or GCP.
- Strong analytical thinking, problem-solving, and stakeholder management skills.
- Excellent communication, storytelling, and executive presentation abilities.
Preferred Qualifications
- Experience with Microsoft Fabric, Databricks, Copilot technologies, or machine learning platforms.
- Knowledge of Generative AI, LLM applications, prompt engineering, and AI automation workflows.
- Experience leading enterprise-scale analytics modernization or digital transformation initiatives.
- Familiarity with Agile methodologies and product operating models.
- Experience supporting Sales, Revenue Operations, or Commercial Intelligence organizations preferred.
Success Metrics
- Accelerated business decision-making through timely, actionable insights.
- Increased automation and analytics efficiency through AI innovation and modern analytics solutions.
- Delivery of scalable, high-quality dashboards, reporting, and data products.
- Improved stakeholder satisfaction and cross-functional collaboration.
- Enhanced adoption of self-service analytics and AI-enabled capabilities.
- Measurable business impact through scalable, governed, and insight-driven solutions.
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