Top Tech Jobs & Startup Jobs

Sell Faire to independent retailers across the UK and Ireland. Own full sales cycle: prospect, qualify, outreach, demo, negotiate and close. Build and manage pipeline using data and AI tools, handle objections, map complex deals, and represent retailer needs internally.

The Staff Product Manager will drive pricing strategies and build tools for pricing performance, collaborating with teams to support brand success and growth.

Lead Finance Systems & Data, driving modernization and AI adoption in finance. Manage architecture, oversee data integrity, and develop a high-performing team.

Build and scale growth systems across the stack to drive retailer acquisition, onboarding, and engagement. Own end-to-end projects, implement experimentation and personalization infrastructure, design reliable services and APIs, instrument and analyze metrics with Data Science, and optimize user experiences for performance and conversion.

The Fraud Strategy Lead will manage strategic fraud initiatives, partner with teams to enhance fraud tools, and mentor junior members, all while advancing fraud capabilities aligned with company objectives.

The Marketing Analytics Senior Lead will manage the analytics strategy for Lifecycle & CRM marketing, influence investment decisions, lead experimentation, and provide insights to enhance marketing efficiency across a global platform.

Provide executive-level support to five Brand leaders across time zones: manage complex calendars, run team operating rhythms, take meeting notes and track deliverables, plan onsites and events, prepare leaders for meetings, act as liaison with stakeholders, and use tools (G-Suite, Slack, AI) to drive efficiency while maintaining confidentiality and prioritizing shifting demands.

Own Faire's ML platform architecture and standards across training, inference, feature management, governance, and MLOps. Architect scalable Databricks/Spark/Delta Lake/MLflow workflows, optimize cost and reliability, integrate LLM workflows, mentor engineers, and lead cross-functional initiatives to increase data science velocity.

Design and operate a scalable ML platform for model training, deployment, and governance while optimizing performance and supporting data scientists in productionizing workflows.