We’re proud to be exclusively partnering with an Innovative Tech Company that’s building a game-changing platform at the intersection of retail analytics and generative AI. This product-led business is on a mission to revolutionise how retailers extract, visualise, and act on data. This role is ideal for a senior data scientist who deeply understands retail data, particularly sales, stock, and range and wants to help shape a product that delivers practical, real-world impact. You’ll be joining a groundbreaking, well-funded Tech Co. that is building a team of smart innovators where your collaboration and contribution matter. You’ll get autonomy, ownership, and the chance to help shape a product with huge potential. If you're curious about AI, excited by product-building, and grounded in retail, this is your kind of role. Role Description A permanent Senior Data Scientist, based in Melbourne or Sydney, with flexibility on working arrangements. In this role, you will analyse retail data to uncover insights, create strategic data models, prepare reports, and collaborate with key business stakeholders to support data-driven decision-making. You’ll be responsible for identifying trends, improving retail processes, and delivering actionable insights to enhance customer experiences and drive business performance. Work directly with a technical founder to build and scale a next-generation retail analytics & GenAI data platform Operate as a highly hands-on Senior Data Scientist, owning delivery for the first 12 months, with potential scope to build out a team. Design and develop large-scale Python / PySpark models across complex retail datasets Own the end-to-end model lifecycle from data ingestion and processing through to model runs, optimisation, and deployment Build statistical and machine learning models focused on retail use cases (pricing, demand forecasting, merchandising, inventory) Work at the intersection of LLMs and retail data, preparing, enriching, and structuring data to enable LLM-driven insights, without needing to build or train LLMs directly Lead data processing, cleansing, and enrichment, treating data as a core platform asset Work across data analysis and data engineering boundaries. Collaborate closely with engineering and DevOps to productionise models and ensure robust, scalable systems Bring strong opinions on tooling, frameworks, and best practices across data processing and AI environments Leverage deep retail domain knowledge (buying, merchandising, category management) to shape high-impact solutions. Be naturally curious and creative, constantly exploring how data, statistical modelling, and retail context can enhance LLM outputs. Thrive in a fast-moving build environment, with a genuine interest in working in an agile, tech start-up, where your ability to contribute, collaborate, and bring energy to an entrepreneurial team is essential. #J-18808-Ljbffr