You will build and lead the UK field operations team responsible for installing and maintaining shelf cameras at retail partner sites. Additionally, you will define operational strategy, manage budgets, and ensure high-quality service delivery through data-driven performance tracking.
You will own the end-to-end analytics architecture, including the data warehouse, transformation layer, and BI tooling. Additionally, you will lead and mentor a team of analysts while partnering with cross-functional stakeholders to define key business metrics.
You will own the product direction for the full data path, managing how retailer data is ingested, processed, and transformed into actionable insights. This involves collaborating with engineering and data science teams to build scalable data products that drive retail operations.
You will lead a senior data team to build and maintain robust, customer-facing reporting pipelines and data platforms. This involves ensuring data accuracy, optimizing compute costs, and partnering with cross-functional teams to deliver reliable intelligence.
Design, operate, and improve core infrastructure including cloud platforms, data pipelines, and observability systems. Focus on scaling backend infrastructure to handle millions of images while reducing costs and latency.
Build and maintain scalable backend services and REST APIs using Python to process data from thousands of IoT devices. Develop and refine frontend features using React and TypeScript to bridge the gap between backend capabilities and user experience.
The role focuses on driving the adoption of AI retail solutions by managing customer onboarding and removing operational barriers. You will act as a strategic advisor to maximize ROI and influence the product roadmap based on customer feedback.
Lead high-quality deployments and own the end-to-end onboarding and integration process for new retail customers. Build tooling to automate manual deployment tasks and troubleshoot complex issues within a distributed AI system.
Own end-to-end analytical problems by combining statistics and machine learning to improve retail AI product performance. Partner with cross-functional teams to define metrics, build predictive models, and deliver actionable insights.
