
Senior Analyst - Product Experience
- Sydney, NSW
- Permanent
- Full-time
- Define requirements for our data collection infrastructure, working with Engineering and Data Engineering to ensure high-quality tracking implementation across our platforms.
- Validate tagging and event instrumentation using tools such as Snowplow Inspector, and other debugging tools to ensure events fire correctly and consistently.
- Collaborate with Frontend and Backend Engineers to translate product requirements into robust, scalable tagging solutions that adhere to our data model and support downstream analytics.
- Drive adoption of analytics and reporting by ensuring tracking and measurement are integrated into the Definition of Done for product features.
- Partner with business stakeholders and product development teams to deliver actionable insights, reports, and research. Key collaborators include Product Owners, UX, and CX teams.
- Lead analytics for our A/B testing capability by working closely with UX, Data Engineering, and Frontend Engineering teams to design, execute, and evaluate experiments.
- Support the evolution of our analytics stack and contribute to the development of our self-service data platform, ensuring high data quality and usability for business stakeholders.
- Promote a product-led mindset by embedding analytics into the product lifecycle and advocating for data-informed decision-making across teams.
- Map customer journeys using behavioural data and provide actionable insights to UX and CX teams to inform design and improve the customer experience.
- Operate as part of a globally distributed team, working with stakeholders across the EU and Australia, and managing your time with autonomy and flexibility.
- Strong domain knowledge in B2C sports betting, with an understanding of the nuances of sportsbook user experience, betting mechanics, and industry-specific data flows.
- Deep expertise in digital data collection and modelling, including the ability to design and evaluate tracking strategies aligned to product and business needs.
- Strong collaboration skills with Data Engineering teams, including defining requirements, coordinating on implementation, and ensuring data quality and usability across shared systems.
- Technical proficiency in tools and languages such as SQL, DBT, Redshift, S3, and Python for data analysis. Familiarity with data visualization and reporting platforms such as Power BI.
- Hands-on experience with event data pipelines, particularly with technologies like Snowplow, to capture and process granular user interactions.
- Experience implementing or working with A/B testing frameworks such as GrowthBook, with a sound understanding of experimental design, segmentation strategies, control group logic, and post-test interpretation of results.
- Familiarity with analytics suites (e.g. Adobe Analytics, Google Analytics). While not essential, this experience will inform your ability to shape the development of our in-house analytics suite, with your insights feeding directly into self-service platform requirements.
- Experience working with cloud-based data platforms within environments such as AWS, Azure, or GCP, including knowledge of data storage, processing, and access controls.
- A growth mindset, demonstrated by a commitment to continuous learning and a willingness to coach, support, and challenge your team to reach their full potential.