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# Senior Data & Insights Analyst

- **Company:** Zero100
- **Location:** London, United Kingdom
- **Experience:** Expert
- **Salary:** £75,252
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Artificial Intelligence, Business Analytics Applications, Data Analysis, Information Engineering, Data Visualization, Python (Programming Language), Microsoft PowerPoint, SQL Databases, Workflow Management Systems, Large Language Models, Databricks
- **Published:** November 13, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5963459556

## About the Role

We're looking for someone with strong analytical fundamentals who has developed practical working habits with AI tools. You should know what good analysis looks like well enough to recognize when AI-generated output is useful, when it needs refinement or validation, and when it shouldn't be relied upon. We're looking for someone who sees these tools as part of a rigorous analytical workflow, not a substitute for structured thinking, sound judgment, or domain understanding. We are less interested in AI courses or certifications and more interested in how you actually use these tools in your analytical work.

The right candidate has experience translating data into insights for senior stakeholders, not just building dashboards. A comfort with ambiguity, structured thinking, willingness to work across diverse problem spaces, and strong communication skills is important. You'll help shape what we investigate and bring forward original insights, with customer-facing work growing as you settle into the role.

Beyond the day job, we are looking for candidates who share our enthusiasm about the potential for Zero100 to have a positive impact on the supply chain profession and (more broadly) the planet., * 5-7 years of experience in data analysis, insights, or a related field, with a track record of presenting findings directly to senior or executive audiences.

 * Note: if the majority of your last two years has been spent building or maintaining dashboards, pipelines, or reporting infrastructure, this is not the right role for you.
 * Strong analytical fundamentals: SQL required, Python a plus; willingness to work in environments like Databricks.
 * Experience producing data visualizations and charts (Excel/PowerPoint, or directly from analytical tools) that make an argument, we care about what a chart proves, not how it looks.
 * Working familiarity with AI-assisted analysis and workflow tools, with a genuine curiosity about where they help and where they fall short. You use AI tools daily in your own analytical work, can describe specific instances where they changed how you approached a problem, and know how to check their output before relying on it.
 * Structured thinking and comfort with ambiguity. You can take a loosely scoped question, decide what matters, and get to a clear point of view independently.
 * Strong collaboration skills. You work well embedded within a research team and can navigate a matrixed, geographically distributed organization.
 * Excellent written and verbal communication skills - you can present data and findings in a way that would resonate with a senior or executive audience.
 * Familiarity with operations or supply chain is a plus, but curiosity and fast learning matter more.

## Description

* Answer specific business questions posed by customers, the Research team, and senior analysts (open-ended or loosely scoped requests), turning them into structured analysis that ends in a clear finding and a recommendation.
 * Transform complex datasets into clear, insight-driven narratives for executive audiences.
 * Support scoping of data needs for new analyses, partnering with data engineering on pipeline work and owning transformation, analysis, and visualization end to end.
 * Maintain a high bar for accuracy and clarity in the insights you deliver.
 * Work across structured and unstructured sources (survey data, executive interview transcripts, operational datasets, and qualitative research notes) to support insights that wouldn't surface from any single source alone.
 * Leverage AI tools (including our internal LLM) to accelerate analysis and explore data, with an eye toward validating and refining output rather than taking it at face value.
 * Collaborate closely with research, design, and customer-facing teams to understand stakeholder needs and deliver reliable, high-quality work.
 * Identify opportunities to surface new insights and propose new lines of inquiry, owning the analytical narrative.
 * Review and raise the quality of work from more junior analysts.