Data Analyst, Spotlight Sports Group

• Strong SQL skills, with the ability to query, join, and manipulate large and complex datasets
• Strong working knowledge of Python for data analysis and automation (e.g. pandas, numpy)
• Ability to understand new datasets quickly and extract meaningful insights
• Experience working with large, complex datasets across multiple sources
• Proficiency in data visualisation tools (Looker Studio), with a focus on creating actionable insights rather than static reporting
• Hands-on experience with product analytics tools (e.g., Google Analytics, Amplitude, Mixpanel)
• Ability to work independently, defining topics for analysis and driving them to completion
• Strong communication skills, with the confidence to present findings and challenge assumptions
• Background in Mathematics, Statistics, Data Science, or a related quantitative discipline

Desirable

• This Data Analyst role sits within the Data Intelligence Unit (DIU) and is focused on insight generation, analytical problem-solving, and decision support, not just reporting
• The role is responsible for improving the organisation’s understanding of customers, behaviours, and performance drivers by moving beyond surface-level trends to explain underlying causes, quantify impact, and support evidence-based decision-making across Content, Commercial, CRM, Product, and Leadership teams
• This role is particularly well suited to an analyst who enjoys working with complex behavioural data, thrives in ambiguous problem spaces, and wants to influence strategy through rigorous analysis
• An interest in sport and betting markets is helpful for context, but analytical curiosity and critical thinking are essential
• Insight Generation: Go beyond BAU reporting to proactively identify trends, patterns, and opportunities in customer behaviour, lifecycle progression, segmentation, and product engagement, linking insight to commercial and strategic outcomes
• Stakeholder Collaboration: Work closely with squads, product teams, and leadership to understand challenges, shape hypotheses, and deliver insights that influence strategic decisions
• Data Storytelling: Translate complex datasets and analysis into clear, compelling narratives that drive action, ensuring insights are accessible and meaningful for stakeholders with varying levels of data fluency
• Impact Measurement: Develop and implement robust measurement frameworks, including test-and-learn approaches, to evaluate the success of business changes and ensure decisions are evidence-based and continuously refined
• Championing a Data-Driven Culture: Advocate for data as a strategic asset, challenging assumptions and embedding insight-led decision-making across Content, Product, CRM, and Commercial teams.
• Automation for Efficiency: Streamline and automate recurring reporting and analysis, maximising time spent on high-value insight generation rather than manual data preparation