About the role

The analyst will audit, cleanse, and standardize product catalogue data to ensure accuracy and consistency across attributes. They will also utilize AI-assisted tools for data enrichment and apply validation rules to maintain high-quality master data.

What they look for

Data cleansing Data quality Product data Data taxonomy Excel Google Sheets SQL Python AI tools ChatGPT PairD Data validation Data reconciliation Category mapping Analytical skills Problem-solving

Requirements

Candidates should have proven experience in data cleansing, data quality, and taxonomy management with strong proficiency in Excel, SQL, or Python. The role requires excellent attention to detail and the ability to work independently within short, focused delivery sprints.

Full description

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.

Interested?

If you have strong product data, data quality or data cleansing experience and are comfortable working with both traditional data tools and AI-assisted workflows, we’d love to hear from you.