Learning Data Specialist 6 month initial hybrid role working from one of our Regional Centres You must have demonstrated experience in data analysis, reporting, and visualisation, within an educational or training environment. Position Overview The Learning Data Specialist is responsible for collecting, analysing, and interpreting data to enhance, learning, and organisational decision-making. This role supports the development of data-driven approaches to improve learner engagement, personalise learning experiences, and measure the effectiveness of learning programmes. The specialist will play a key role in leveraging learning analytics and data to foster a culture of continuous improvement and innovation. Key Responsibilities Data Collection and Management Design and implement processes for collecting and maintaining high-quality data from learning management systems (LMS) and other learning technologies used across HMRC. Ensure data integrity, accuracy, and compliance with HMRC and legal requirements (e.g., GDPR). Develop and maintain dashboards and reporting tools for stakeholders to access and interpret learning data. Data Analysis and Insights Conduct detailed analyses of learning data to identify patterns, trends, and areas for improvement. Use predictive analytics to support student success initiatives, such as identifying at-risk learners. Provide actionable insights to learning specialists and leadership to inform decision-making. Technology Integration Work closely with IT, Learning Technology, and Academic Teams to integrate learning analytics tools and systems into the institutions digital infrastructure. Collaborate with system vendors to ensure optimal functionality and performance of learning data tools. Evaluate and recommend new technologies and methodologies for learning data collection and analysis. Stakeholder Engagement Partner with learning leads and instructional designers to help them understand and use data to improve course design and delivery. Deliver workshops, training, and resources to build organisational capacity in understanding and applying learning analytics. Collaborate with leadership to develop data-informed strategies for curriculum development, learner support, and institutional performance improvement. Compliance and Ethics Ensure compliance with all relevant regulations regarding data privacy, protection, and ethical use. Promote the ethical use of learning data, ensuring transparency and fairness in analytics and AI-driven initiatives. Person Specification Essential Qualifications and Experience A degree in Data Science, Educational Technology, Statistics, Computer Science, or a related field. Demonstrated experience in data analysis, reporting, and visualisation, preferably within an educational or training environment. Proficiency in data tools and platforms such as SQL, Power BI, Tableau, Python, R, or similar. Familiarity with learning management systems (e.g., Moodle, Kallidus) and their data structures. Desirable Qualifications and Experience A postgraduate qualification in Data Analytics, Learning Technologies, or a related field. Experience with machine learning, AI, or predictive modelling in an educational context. Knowledge of institutional research and quality assurance processes. Skills and Attributes Strong analytical skills, with the ability to translate complex data into actionable insights. Excellent communication and presentation skills, including the ability to explain data findings to non-technical audiences. Problem-solving mindset with attention to detail and a focus on continuous improvement. Ability to work collaboratively across multidisciplinary teams and with diverse stakeholders. Knowledge Understanding of learning analytics frameworks and best practices. Knowledge of data privacy regulations (e.g., GDPR) and ethical standards for data use in education. Awareness of emerging trends in learning analytics and educational technology. Key Performance Indicators (KPIs) Timely delivery of accurate and actionable data reports and dashboards. Positive feedback from stakeholders on the utility and clarity of analytics outputs. Demonstrated impact of data insights on learner engagement, retention, and outcomes. Successful implementation and adoption of analytics tools and methodologies across the organisation.