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Job title: Data Analyst
Start Date: ASAP
Contract: six months (possibility of extension)
Location: Paddington (Hybrid)
Sector: Retail
Summary
Producing an analysis is only part of the job; understanding whether it can be trusted, explained and used to support a decision is just as important.
Our Advanced Analytics team helps make better decisions by combining commercial insight, decision science and analytical engineering. We work across product squads and the wider business on trusted, high-impact analytical solutions.
As a Data Analyst, you'll contribute across the analytical process, from preparing and exploring data through to statistical modelling, experimentation, impact evaluation and communicating results. You'll work with business and product teams to investigate complex commercial questions and generate robust evidence.
This role would suit someone with strong statistical knowledge who is excited by applying it to real-world problems. You don't need extensive commercial experience, but you should bring curiosity, experience using data, exposure to advanced methods and a desire to develop in a business environment.
What You'll Do
Your key accountabilities will include:
- Contribute to analytical work on high-value opportunities, collaborating with experienced analysts, data scientists, product teams and business stakeholders to support better decisions.
- Help translate complex or ambiguous business questions into clear analytical objectives, success measures and structured analysis plans.
- Prepare, explore and analyse data to understand performance, identify meaningful patterns and drivers, and uncover opportunities to create measurable business value.
- Support the design and application of appropriate approaches, including statistical modelling, experimentation and quasi-experimental methods, to test hypotheses, evaluate initiatives and quantify their impact.
- Validate analytical outputs and communicate findings, uncertainty and limitations clearly, helping stakeholders understand what the evidence does and does not support.
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Who You Are
Your skills and experience will include:
- Strong mathematical and statistical knowledge, including familiarity with probability, statistical inference, regression, experimental design and the interpretation of results.
- Exposure to advanced analytical and/or machine learning methods through study, research or practical experience, with an interest in understanding when different approaches are appropriate and what their limitations are.
- Strong analytical problem-solving skills, with the curiosity and structured thinking needed to investigate unfamiliar or ambiguous questions using imperfect real-world data.
- A clear communicator who can explain analytical approaches and findings to others, with the potential to develop this skill further when working with non-technical audiences.
- Experience using at least one data-focused programming or analytical language, such as Python, R, SQL, PySpark or similar.
Role is placed within the Advanced Analytics function, supporting the strategic Insights Engine programme.
The project aims to move retail colleagues away from consuming large volumes of reports and towards AI-enabled, prescriptive, exception-based insights that highlight where intervention is required and measure the business impact of those actions.
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The key hiring requirement is an analyst with strong experimentation, evaluation and statistical analysis skills, particularly around measuring intervention effectiveness through A/B testing, quasi-experimental methods, and stakeholder-facing insight delivery.
Key Responsibilities
- Analytical discovery and opportunity identification.
- Value case assessment.
- Data preparation and ETL support.
- Feature engineering collaboration with Data Scientists.
- Testing and evaluation of interventions.
- Experiment execution and results analysis.
- Presenting outcomes to senior stakeholders.
- Influencing business decisions through analytics.
Must-Have Skills
Technical
- Statistical modelling.
- A/B testing experience.
- Experimental design understanding.
- Difference-in-differences or similar quasi-experimental techniques.
- Data analysis and interpretation.
- Ability to execute analytics frameworks designed by senior analysts.
Business
- Stakeholder communication.
- Translating analysis into actionable business recommendations.
- Working within cross-functional teams.
Nice-to-Have Skills
- Exposure to Data Science environments.
- Retail analytics experience.
- Experience working alongside Product Managers, Data Scientists and Data Engineers.
- Broad analytical toolkit across multiple techniques.
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