Senior Data Analyst

Xero
UK: London (7 Devonshire Square)Posted 4 March 2026

Job Description

Senior Data Analyst Our Purpose Planday from Xero is a leading digital solution that uncomplicates everyday scheduling and workforce management by making it easier for businesses and shift workers around the world to communicate, collaborate, and get work done. Powered by a community of local industry experts, Planday provides a best-in-class digital platform that is easy to use, accurate, secure, and compliant with local needs and standards. From payroll and accounting to POS and reporting, its open API and tech ecosystem is scalable to fit shifting business needs and to build an engaged, flexible workforce. Founded in 2004, Planday is headquartered in Copenhagen, Denmark and supports over 400,000 users across Europe, Australia and the US. Planday was acquired by Xero in 2021. How you’ll make an impact As a Senior Data Analyst, you'll play a strategic role in transforming complex data into actionable insights that directly fuel our business growth and critical decisions. You'll craft compelling data narratives, turning raw information into valuable assets that guide product development and key strategic choices. Collaborating across teams, you'll uncover pivotal metrics and deep customer insights, empowering informed decisions throughout Planday. Through impactful visualizations and persuasive communication, you'll ensure these insights resonate with stakeholders at all levels. Finally, you'll leverage advanced analytical techniques to pioneer predictive modeling and automation, fostering a culture of data-driven innovation that is central to Planday's continued success. What you’ll do You’ll be instrumental in: - Collaborating cross-functionally with product, commercial, and leadership teams to define, track, and report critical metrics, delivering comprehensive customer insights. - Designing and maintaining robust data models that transform raw data into high-value assets, ensuring accuracy and quality. - Developing impactful, hands-on solutions, visualizations, and dashboards across the business, primarily utilizing Tableau to communicate insights effectively. - Leveraging expert proficiency in Python, R, and SQL for advanced data manipulation, statistical analysis, and ensuring high data quality. - Applying advanced statistical analysis techniques for summarizing, interpreting, and predicting data, alongside machine learning concepts for predictive modeling techniques. - Translating complex data into clear, actionable narratives through compelling data storytelling, impactful presentations, and strong interpersonal communication. Success looks like Your success will show through: - Exceptional data models that consistently deliver accurate, high-quality data assets, underpinning strategic initiatives. - Proactive delivery of actionable insights and critical metrics that directly lead to informed decisions and tangible business improvements for product and commercial teams. - Development and implementation of intuitive and highly impactful visualizations and dashboards that significantly elevate data-driven decision-making across Planday. - Insights and recommendations that are consistently trusted and acted upon by product and commercial teams, stemming from rigorous analysis and robust data practices. - Clear and compelling communication of complex data insights, fostering understanding and alignment among stakeholders, resulting in measurable positive business impact. - Proactive problem-solving and innovative thinking in addressing data-related challenges, leading to continuous improvement and advancement in our analytical capabilities. - Successful exploration and implementation of advanced analytical techniques, including machine learning, to unlock new opportunities and generate groundbreaking insights. What you’ll bring with you You'll be an expert with: - Proven expertise in Python, R, and advanced SQL (including window functions, CTEs) for data management and statistical analysis. - Pro ... (truncated, view full listing at source)
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