Product Analyst

We are looking for a meticulous and curious Product Analyst to join our Product Operations team, with a focus on providing robust analysis of our data source quality, defining metrics and reporting to generate actionable insights that drive decision making and trust in the data that powers our products and services.
As we expand our data sources, we need to understand their relative quality and depth to help us prioritise and harmonise product data in a way that provides the most insightful benefit for our clients. This role will work cross-functionally across our product teams and with key internal stakeholders, providing regular updates as well as targeted support and insight as required.
The role will work closely with the Label Insight Data Governance Team, situated in our Product Team. The team is dedicated to ensuring the quality, integrity, and usability of data across the organization. Comprising three specialized teams—Attribute Health, Source Quality, and Data Support—it works collaboratively to uphold robust data standards, validate AI-generated outputs, and provide responsive, client-focused support. Together, the team enables scalable, trustworthy, and insight-ready data that powers our products and services.
Key Responsibilities:
Evaluate the relative and overall quality of our data sources including data produced by AI models, web scraping, manual coding, and other coded sources
Define and implement metrics that provide actionable insights to both improve data reliability and quality, and help support prioritisation and harmonisation of our data sources
Provide consistent reporting on data source quality – using dashboards and reports to communicate trends and issues, and proposed actions to address
Identify anomalies, patterns, and potential risks in these data sources, with a key focus on ensuring the confidence of AI-generated data
Design and implement methods to detect outliers, inconsistencies, and unexpected trends in data sources
Investigate root causes of anomalies and collaborate with technical teams and key stakeholders to address underlying issues
Support the application of validation rules, checks, and metrics to monitor data quality over time
Collaborate with data scientists and engineers to refine AI outputs based on quality findings
As needed, support taxonomy recognition tasks to ensure our attributes achieve the required quality thresholds
Experience in data analysis, data quality essential
Experience working with AI/ML-generated data beneficial
Strong skills in SQL and data visualization tools (e.g., Power BI, Tableau)
Experience with anomaly detection techniques and tools is highly desirable
Understanding of AI/ML concepts and how data flows through models
Excellent attention to detail, analytical thinking, and communication skills

Employment type
Full-time

Work arrangement
No