Top Tech Jobs & Startup Jobs

Build scalable data pipelines, dimensional data models, automated reconciliations, transaction controls, dashboards, and analytics across e-commerce, tax, customs, finance, logistics, and supply-chain systems. Improve data quality, lineage, auditability, and exception detection while exploring automation, machine learning, and AI use cases.

Develop and deploy scalable machine learning models and intelligent systems for ASOS. Apply machine learning, statistics, optimisation, and experimentation to solve business problems, evaluate model and business impact, and productionise solutions with engineering partners. Collaborate with data engineers, ML engineers, analysts, product managers, and stakeholders while contributing to applied research, technical direction, MLOps practices, and knowledge sharing.

Leads and grows an AI engineering team while remaining hands-on with agentic AI and automation development. Owns technical direction, engineering standards, delivery, production operations, monitoring, incident response, and stakeholder engagement. Builds production-ready AI agents integrated with finance, commercial, buying, merchandising, and data platforms using retrieval augmented generation and tool orchestration. Partners with the central AI team to follow governance, measure business impact, and deliver reliable automation.

Leads product analytics for ASOS, using customer funnel analysis, experimentation, A/B testing, dashboards, and statistical methods to guide product strategy and improve conversion, engagement, and retention. Partners with Product Managers and senior stakeholders to define success metrics, identify growth opportunities, translate complex data into actionable narratives, and influence roadmaps. The role also mentors junior analysts and promotes data-driven decision-making and analytical best practices.

Leads strategic, cross-functional logistics, supply chain, and operational change projects from scoping through delivery and handover. Manages scope, schedules, budgets, resources, risks, vendors, governance, stakeholders, and benefits realization. Presents updates to senior leadership, supports operational transition, mentors project managers, and improves project delivery processes. Requires logistics or supply chain experience, strong financial and risk management, stakeholder leadership, and willingness to travel up to 50%.

Manage and optimise ASOS websites and apps through digital merchandising, navigation, onsite search, ranking, homepage, promotional and campaign strategies. Partner with Digital Trading, Pricing, Trade Marketing and Tech teams to improve customer journeys, conversion and sales. Lead Digital Trading Assistants, maintain site quality, support feature rollouts, troubleshoot issues, and contribute to team development and strategic initiatives.

Supports the day-to-day trading and optimisation of ASOS websites across devices and markets. Responsibilities include site merchandising, search optimisation, category and navigation management, trade reporting, customer journey analysis, homepage and promotional coordination, campaign launches, and digital product rollouts. The role works cross-functionally to improve onsite experience, commercial performance, and conversion while maintaining website standards.

Build and operate FinOps data platforms, cost pipelines, allocation models, Power BI semantic models, and cloud optimization tooling across ASOS’s Azure estate. Develop production services with Python, Databricks, Azure Functions, Bicep, and CI/CD. Partner with engineering and finance teams on cost attribution, forecasting, guardrails, unit economics, and architecture decisions. Provide technical leadership through design reviews, mentoring, and code reviews while ensuring reliability, security, and compliance.

Design and industrialize production-grade AI and LLM platforms for ASOS. Build RAG systems, fine-tuned models, agentic workflows, orchestration layers, evaluation frameworks, vector retrieval pipelines, and AI safety guardrails on Azure. Develop reusable capabilities that scale across teams, optimize performance, cost, and reliability, and partner with security stakeholders on governance and responsible AI.

Designs, builds, and operates scalable machine learning platforms supporting training, deployment, inference, search, recommendations, and personalization. Responsibilities include cloud-native infrastructure, backend services, CI/CD, observability, automation, distributed computing, Infrastructure as Code, incident management, and architectural leadership. The role collaborates with data scientists, engineers, and product managers, owns production reliability, mentors engineers, and shapes long-term MLOps and AI platform strategy.