Data Analyst Higher Level Apprenticeship - PreWarp
About PreWarp:
PreWarp was born from a simple but persistent problem heard across the fashion and apparel industry. PreWarp solves this by delivering the first and only truly “out of the box” solution for harmonising global wholesale sales data without complex integrations. Our AI-powered technology automatically consolidates and standardises sales and product information from over 100 retailers globally, giving brands a single source of truth for in-season performance.
Today, brands including Stella McCartney, Victoria Beckham, Canada Goose, Antler Luggage, and Rixo use PreWarp to gain accurate, timely insights and drive better decisions across merchandising, sales, retail, and e-commerce. Our platform saves teams hours every week by automating previously manual reporting and unlocks commercial opportunities that would otherwise be missed.
We are a small but dynamic team with experience spanning fashion technology, wholesale, merchandising, and advanced data science and engineering (including Formula 1 backgrounds). As a start-up at an early but exciting stage, we are hands-on, collaborative, and supportive. No two days are the same - you’ll be exposed to all parts of the business, contribute meaningfully to our growth, and help solve real problems for brilliant clients. We work hard, stay curious, and don’t take ourselves too seriously.
Overview:
We are looking for a motivated and detail-oriented Level 4 Data Analyst Apprentice to join the PreWarp team. This is an opportunity to gain hands-on experience in real-world data analysis while completing a formal apprenticeship programme.
You will work closely with our data, engineering and commercial teams, helping maintain the accuracy of retailer data, supporting reporting workflows, and assisting with investigations when numbers don’t look quite right. You’ll learn how our AI-driven harmonisation technology works, how global retail data is structured, and how to diagnose and resolve common data issues faced by leading fashion brands.
This role is ideal for someone with a passion for numbers, problem-solving, and structured thinking. No industry experience is required, but any start up or data handling experience is a plus - predominantly we value curiosity, attention to detail, and a willingness to grow.
Responsibilities:
* Data quality & account maintenance: Carry out regular account health checks to identify issues such as missing data, unusual pricing, mismatched seasons, or incorrect product attributes within the PreWarp platform. Take ownership of routine account fixes, including resolving negative sales records and ensuring doors, seasons, and product fields are mapped correctly across retailers. Maintain consistent and accurate data by applying PreWarp’s mapping rules and harmonisation
* Data investigation & problem-solving: Support in diagnosing data issues raised by internal teams or clients, reviewing calculations and data flows to understand why numbers may appear incorrect. Produce clear, client-friendly Excel summaries explaining how figures were derived or highlighting where genuine errors were identified. Assist during time-sensitive in-season selling investigations.
* Data processing & reporting: Support weekly and monthly reporting cycles to ensure data is cleaned, validated, and ready for internal and external use. Update dashboards and ensure all selling metrics and KPIs reflect the latest data. Follow established workflows to contribute to PreWarp’s “single source of truth”.
* Platform, product & engineering support: Work with product and engineering colleagues to test new data features, identify edge cases, and flag potential issues before release. Contribute to improving internal processes by documenting tasks, mapping logic, and data Help refine platform behaviour by spotting recurring data inconsistencies or frequently misunderstood metrics.
* Optional stretch projects (interest-based): Explore OCR techniques to support automated extraction of retailer PDFs. Experiment with entry-level machine learning approaches for data reconciliation. Present findings and support exploratory model-improvement work.
* Cross-team collaboration: Work with commercial, product, and data teams to understand their information needs and support internal decision-making with accurate data. Contribute to ad hoc analyses and structured problem-solving tasks. Assist in preparing data summaries or materials for clients (with internal review).
* General start-up support: Support wider operational tasks during busy periods, reflecting PreWarp’s collaborative, hands-on culture. Help prepare materials and insights for internal meetings. Contribute across different parts of the business, gaining broad exposure to how a technology start-up scales.
Desirable skills:
* Strong attention to detail and a problem-solving mindset.
* Good numeracy and analytical skills.
* Basic knowledge of Excel is useful; familiarity with SQL or Python is a plus, but not essential.
* Curious and eager to learn new tools and techniques, including how data is structured in global fashion retail.
* Effective communication skills, both written and verbal.
* Ability to work independently and as part of a collaborative team.
* Comfortable working in a fast-moving start-up environment where priorities can shift.
Entry requirements:
* Standard entry: Level 3 qualification (apprenticeship/A-levels/BTEC, etc) OR equivalent work experience (typically two years in a relevant role)
* Plus: 5 GCSEs, including English and Maths at Grade 4 (C) or above
* Experience with using Excel and Microsoft products (or similar)
* You may also have a combination of qualifications and experience which demonstrate the minimum foundation needed for the programme. In this instance you could still be considered for the programme.
* If you hold international equivalents of the above qualifications, at the time of your application you must be able to provide an official document that states how your international qualifications compare to the UK qualifications.
Working hours:
9am – 5:30pm.
Benefits:
* 27 days annual leave allowance.
* Pension scheme.
* Private medical (which included gym discount and other perks).
* Cycle to work scheme.
Future prospects:
90% of QA apprentices secure permanent employment after completing: this is 20% higher than the national average.
How to apply
To apply for this role and to find out more, please click on the apply button. Please note that applications may close before the application deadline, so apply early to avoid disappointment.