Product Data Quality Analyst – Data Cleansing & Standardisation
Summary
A remote, short-term contract role at Deloitte auditing, cleansing and standardising a product catalogue so every SKU has complete, consistent attributes. The analyst applies taxonomy rules, uses AI tools (e.g. ChatGPT, PairD) for enrichment suggestions, and validates data with SQL/Python and Excel, working in short delivery sprints under IR35 via Rockford Payroll.
This is a remote position.
Role: Product Data Quality Analyst – Data Cleansing & Standardisation
Location: Remote
Start Date: 2 weeks time
End Date: TBC
Daily Rate: Competitive, Inside IR35, Rockford Payroll Info for Contingent Workers – Rockford Pay
Contract | Remote | Short-term assignment
We’re looking for an experienced Product Data Quality Analyst to support an important data quality and standardisation project.
You’ll be responsible for reviewing, cleansing and standardising a product catalogue, ensuring every SKU has a complete, accurate and consistent set of attributes. This is a hands-on role for someone who enjoys working with data, spotting inconsistencies and turning complex or messy information into a reliable, structured product master.
The role will also involve using AI-assisted tools to accelerate data enrichment and identify potential attribute values, with human review and validation applied where required.
What you’ll be doing
- Audit and cleanse product catalogue data across multiple attributes, including categorisation, size, colour, material, brand and related product information.
- Standardise inconsistent product data and apply agreed rules and taxonomy structures.
- Map products to the appropriate categories and classifications.
- Use AI-assisted tools to support data imputation, enrichment and candidate suggestions.
- Review ambiguous or potentially incorrect AI-generated recommendations and make informed decisions.
- Develop and apply validation rules to improve data accuracy and consistency.
- Carry out sample-based accuracy and quality checks.
- Reconcile data and identify discrepancies or mismatches.
- Apply confidence scoring to data decisions where appropriate.
- Maintain clear audit trails and document the rationale behind data changes.
- Escalate unresolved or high-impact data quality issues.
- Produce a concise handover document covering data provenance, methodology and known caveats.
- Work within short delivery sprints, following clear SOPs and acceptance criteria.
- Provide regular progress updates throughout the assignment.
What we’re looking for
You’ll ideally have experience in data cleansing, data quality, product data or data taxonomy, with a strong eye for detail and the ability to work confidently with large or complex datasets.
You should have:
- Proven experience in manual data cleansing and data quality.
- Experience with rule-based data normalisation.
- Knowledge of data taxonomy and category mapping.
- Strong Excel or Google Sheets skills.
- Experience using SQL and/or Python for data sampling, validation or reconciliation.
- Experience using AI tools such as ChatGPT, PairD or similar to accelerate data analysis, predictions or candidate suggestions.
- Strong analytical and problem-solving skills.
- Excellent attention to detail and a methodical approach to data validation.
- The ability to distinguish between reliable data and ambiguous or potentially incorrect information.
- Experience working to defined SOPs, acceptance criteria and quality standards.
- Comfortable working independently within short, focused delivery sprints.
Why this role?
This is an opportunity to work on a data transformation and product catalogue quality project, combining traditional data quality and cleansing techniques with emerging AI-assisted approaches.
You’ll play a key role in creating a canonical product master that can subsequently be used for accurate assortment analysis and wider business decision-making.
