Senior Data Analyst

Roles And Responsibilities

• Own and drive data-driven solutions to optimise product performance and overall business outcomes by analysing product, learner, and operational data.
• Execute end-to-end analytics initiatives with high ownership—from problem scoping and data analysis to implementation, evaluation, and stakeholder adoption—ensuring alignment with organisational goals.
• Analyse product and learner journeys to identify performance patterns, drop-offs, and gaps in system and user flows, translating findings into actionable analytical initiatives and product/process enhancements.
• Plan and conduct structured, hypothesis-driven analyses with clearly defined objectives, scope, methodology, and data requirements to ensure unbiased, decision-ready insights.
• Build and maintain analytical frameworks, models, and automations that improve product effectiveness, streamline internal operations, and enable more personalised and efficient learner experiences.
• Monitor and evaluate the impact of implemented analytics solutions, continuously iterating to improve accuracy, relevance, and long-term business value.
• Design and manage monitoring and alerting mechanisms for dashboards, automations, and analytical outputs to ensure reliability and early issue detection.
• Take complete ownership of data accuracy, consistency, and integrity across reports, dashboards, analyses, and automated outputs, ensuring all deliverables are stakeholder-ready.
• Conduct analytical and technical research to enhance methodologies, including forecasting approaches, segmentation logic, feature engineering, and performance measurement techniques.
• Translate complex analytical findings into clear insights, dashboards, and executive-ready recommendations for leadership and cross-functional teams.
• Collaborate with engineering and DevOps teams to deploy and operationalise analytics solutions, supporting version control, monitoring, troubleshooting, and workflow integration.
• Create and maintain comprehensive documentation for data sources, logic, dashboards, automations, and analytical processes to ensure transparency and scalability.
• Partner closely with Product, Academics, Operations, and Business teams to understand context, refine requirements, and ensure analytics outputs are practical and actionable.
• Develop a deep understanding of product offerings, learner journeys, and operational workflows to ensure analytics initiatives are context-aware and high-impact.
• Continuously upskill in analytics tools, techniques, and domain knowledge to stay aligned with evolving best practices and business needs.
  

Education & Experience

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related field
• 4–7 years of relevant experience in data analytics, product analytics, or business intelligence roles
  

Good to Have

• Experience in EdTech, SaaS, or LMS-based platforms
• Exposure to ML concepts such as clustering, forecasting, or predictive modelling
• Familiarity with cloud data environments (BigQuery, Redshift, Snowflake, etc.)
• Experience working with engineering or DevOps teams for analytics deployment