Description
We are looking for a Lead Analyst to join our eCommerce Data team
The Data Team enables the department and the business to elevate understanding of customer behaviours and sales performance - what is working and what is not by articulating actionable insights from complex data.
We value curiosity, inspire ideas and unlock new opportunities. You will access advanced AI tools and data platforms, and grow fast with support.
About the Role
As a Lead Analyst, you will transform our data landscape from reactive into proactive analytics. Success in this role means achieving "Autonomous Insight Discovery" - using AI to detect trends and deliver automated argumentation in minutes rather than weeks.
You will champion a "try fast, fail fast" philosophy, rapidly piloting tools to automate manual data workflows and enhance scalability. You will enable the analytics team not just report numbers; you will deliver AI-driven argumentation, providing instant insights through LLM conversational analytics. Partnering with Trading, Digital Product, and Data teams, you'll bridge the gap between business needs and practical, real-world AI solutions.
Your responsibility is to achieve "Insight Velocity", turning a raw dataset into a validated business hypothesis and reducing time between data anomalies and executive action from weeks to minutes.
Ultimately, success is when a stakeholder asks a complex question—like "What drove the sales performance last week and why ?" We can provide a natural language response that synthesises web behavior, customer data, and market trends instantly to enable analysts to articulate the data story quickly and clearly.
What you'll take on
* AI-Enhanced Business Intelligence: Deliver AI in BI solutions, moving beyond static dashboards to conversational and also predictive and prescriptive analytics that provide "argumentation"—explaining the why behind the data, not just the what.
* Speed to insight: Develop capabilities such as AI agents capable of "talking to data"—allowing non-technical users to query complex databases using natural language to receive instant, visualised insights.
* Rapid Prototyping: Design and test proof-of-concept models using LLMs, computer vision. You'll validate whether a tool delivers high-accuracy insights or if it's just noise, moving on quickly if the value isn't there.
* Automation for Scalability: Build and implement automated workflows that handle data cleaning, anomaly detection, and trend reporting, allowing the team to focus on high-level strategy.
* Innovation Deployment: Help take Al features into production, working with engineers to meet reliability and security needs. Contribute to data preparation and feature engineering for Al use cases.
What you'll bring
* Innovation mindset: Track record of taking vague business problems and turning them into structured AI experiments. A genuine desire to learn fast and grow your skills in applied Al and agentic tooling.
* Problem solving mindset: Intellectual curiosity and problem-solving instincts that drive you to figure things out.
* Experimental mindset: A "fail fast" approach with a focus on high-impact, scalable results.
* Communication:
o Refine the technical requirements to specifically highlight the AI frameworks or prompt engineering skills and then communicate.
o The ability to explain AI logic, visualise complex data findings and articulate model behavior to non-technical stakeholders.
* Technical skills:
o Great SQL and Python skills and the ability to write code that others can understand and maintain.
o Practical knowledge of APIs, services and development practices like version control, code reviews and testing.
o Exposure to GCP, Databricks, Azure Al services or similar cloud Al platforms along with agent frameworks, RAG patterns or orchestration tools are beneficial.
* AI and data pipeline skills: Understanding of basic ML and Al concepts like prompting, evaluation, embeddings and how models and data workflows work.
* Ecommerce and web analytics knowledge: Understanding of key metrics of web analytics and having business acumen for ecommerce.