Online Operations - Content Quality Reviewer

Online Operations - Content Quality  Reviewer Location:  London, UK Length:  12 months Duration: 23/02/2026 – 23/02/2027 Rate: £34.62 per hour (Inside IR35)Hours:  40 hours week Job Description: We are looking for a Taxonomist to support the ecommerce initiatives within the Catalog organization. The crux of this work involves enriching and normalizing product client data, like Brand, into our unified product taxonomy to facilitate machine learning and drive the development of Catalog initiatives. In addition to client data normalization, this role may also involve cross-taxonomy mapping, vertical expansion, front-end taxonomy design, and working closely with engineers to facilitate ML understanding through annotation and evaluating model output.Job Responsibilities:- Detailed data analysis (Excel, Google Sheets or scripting languages) to identify identical and/or fuzzy matches across multiple vocabularies- Research (both internal and external) to enrich node client data- Status reporting on progress, questions, issues, or potential opportunity areas with partners and stakeholders- Implementation based on taxonomy governance guidelines Minimum Requirements:- 2+ years of experience in developing taxonomies/or ontologies to support a variety of systems both for front-end and back-end use.- Experience in building taxonomies or experiences for ecommerce- Experience researching and defining taxonomy client data based on existing standards- Experience with a variety of topic/domain types- Experience communicating and presenting taxonomy principles and standards- Strong ownership and ability to self-start, build relationships with partners, and develop a point of view- Strong ability to proactively communicate about projects and workstreams- Strong affinity for detail-oriented taxonomy development work Preferred Qualifications- Master’s Degree in Library Science or Information Management- Experience in analysing large volumes of data with SQL or other query languages- Experience building taxonomies for machine learning classification systems- Experience with prompt engineering and AI tools