Senior Analyst (Learning Analytics)

About the role

CSC is seeking an experienced Senior Analyst to lead and advance its Learning Analytics practice, supporting evidence-informed decision-making, learning effectiveness and performance-led learning and development. The role combines learning analytics, programmatic evaluation, applied research, stakeholder engagement and data product development, and contributes to adopting AI-enabled approaches in evaluation. It suits someone who balances the rigour of a researcher with the pragmatism of a consultant.

Key responsibilities

• Lead Learning Analytics projects from problem framing and evaluation design through analysis, interpretation, recommendations and implementation.
• Partner with stakeholders to turn learning, capability and performance questions into analytical and evaluation approaches.
• Design and run quantitative, qualitative and mixed-method studies on learning effectiveness, transfer, workplace application, behavioural change and performance outcomes.
• Develop measures, indicators and evaluation frameworks, and analyse structured and unstructured data using psychometrics, multi-level modelling, causal analysis and text analytics.
• Translate findings into narratives and recommendations for technical and non-technical audiences.
• Build scalable data products such as RShiny applications, Tableau dashboards and natural language interfaces.
• Explore AI-enabled approaches including automation, NLP and large language models.
• Act as subject matter expert and represent CSC at conferences and seminars.

Required profile

• Degree in Statistics, Data Science, Economics, Psychology, Learning/Cognitive Sciences, Business Analytics, Programme Evaluation or a related field; Master's preferred.
• At least 5 years of experience in analytics, applied research, data science, consulting or related fields.
• Proven ability to lead analytical projects from framing to implementation.
• Strong stakeholder engagement, facilitation, communication and presentation skills.
• Preferred: experience in Learning Analytics, programme evaluation, workforce capability analytics or performance-led L&D, and presenting research at conferences.

Required skills

• Statistical modelling, psychometrics, causal analysis, survey design, text analytics and data storytelling.
• Preferred: R, Python, Tableau, RShiny, AWS ecosystem, and AI/ML, NLP/LLM tools.