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# Associate Data Analyst

- **Company:** Levi Strauss
- **Location:** London, UK
- **Experience:** Starter
- **Salary:** £39,700.0 - £52,900.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, E-Business, Power BI, Standard Sql, Tableau (Software), Looker Analytics
- **Published:** July 24, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=1c44d2fcd9cf17ae

## About the Role

* 1-2 year's experience in an analytics role, ideally within ecommerce, retail, or a consumer-facing business.
 * Solid SQL skills with a willingness to develop further;
 * Experience building dashboards with a BI tool such as Looker, Tableau, or Power BI.
 * Familiarity with web or app analytics platforms and event-based data.
 * Understanding of experimentation principles and an eagerness to develop statistical literacy.

This is a hybrid position based in our Central London Office. You will be expected to be in the office three days per week, though time in office may vary depending on business needs.

## Description

As an Associate Data Analyst, you'll work alongside experienced analysts to analyse commercial performance, build dashboards, and deliver insights that help optimise customer experience and business performance. You'll collaborate with cross-functional teams to support data-driven decision-making across our digital business., * Diagnose commercial performance through analytics deep dives and statistical analyses, working alongside senior analysts to develop root cause hypotheses and suggest actions.

 * Build, maintain, and iterate stakeholder-friendly dashboards, giving commercial teams to ability to self-serve.
 * Contribute to standardised KPI definitions and flag data quality issues proactively.
 * Conduct experiment analysis to understand the impact of web or app changes on customer experience.
 * Monitor customer trends, escalating anomalies and beginning to develop an intuition for what drives commercial outcomes.
 * Collaborate with product, trading, marketing, and operations teams to support data requests and contribute to decisions grounded in data.
 * Document logic, assumptions, and methodologies clearly to promote transparency and repeatability.


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