Role overview
- Interpret unstructured product descriptions
- Extract key attributes (brand, model, size, etc.)
- Categorise products into structured taxonomies
- Identify duplicate or equivalent products across datasets
This is a technically challenging role involving text processing, data engineering, and intelligent matching, with real-world impact across enterprise and government datasets.
What we're looking for
- Experience with product catalogue data or e-commerce datasets
- Experience with classification and taxonomy systems
- Familiarity with local/offline ML models
- Knowledge of **data quality tools or MDM systems
To Apply:**
Please include:
- Examples of similar work (entity matching, NLP, product data, etc.)
- A brief outline of how you would approach this problem
- Your preferred tech stack for implementation
We are looking for someone who can think, design, and deliver — not just code to a spec.
Job Types: Freelance, Temp to perm
Pay: £25.00-£35.00 per hour
Application question(s):
- How would you approach matching two product descriptions that are written very differently but refer to the same item?
- What techniques would you use to extract structured attributes (e.g. brand, size, colour) from messy product descriptions?
- How would you design a matching score between two products?
- How would you avoid comparing every product to every other product (performance problem)?
Work Location: In person
Tags & focus areas
Used for matching and alerts on DevFound Temporary Machine Learning Nlp Data Engineer Ai