About MediaRadar MediaRadar, equips marketing, sales and analytics leaders with the intelligence they need to stay ahead.
Our platform delivers always-on, AI-enabled Creative, Competitive, Commercial and Market Intelligence—spanning ad strategy, media spend, creative assets and brand messaging across 30+ media channels and five million brands.
With deep insights into more than 35 million ad and campaign assets and $280 billion in media spend, MediaRadar provides a single, interoperable source of truth that plugs seamlessly into enterprise analytics and AI systems.
The result: faster, cleaner and more actionable intelligence that drives competitive advantage.
Job Summary We are seeking a rigorous Data Quality Auditor to provide independent assurance over the accuracy and reliability of our governed data and AI-assisted classification outputs.
In an operating model where AI does the work and people validate it, this role is the assurance layer — sampling, testing, and auditing outputs against defined rules and standards to confirm that quality holds at scale.
This is a lean, high-trust role focused on audit and assurance rather than production.
You will design and run audit programs, quantify quality against measurable thresholds, and give leadership an objective, evidence-based view of data trustworthiness.
You partner closely with Data Operations, Governance, and Engineering while maintaining the independence required to assess quality objectively.
At MediaRadar, we are committed to creating an inclusive and accessible workplace where everyone can thrive.
We believe that diversity of backgrounds, perspectives, and experiences makes us stronger and more innovative.
We are proud to be an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other legally protected status.
In accordance with the EEO-1 reporting requirements, we collect demographic data as part of our efforts to ensure fair and equitable hiring practices across all levels of our organization.
A final compensation offer will ultimately be based on the candidate's location, skill level and experience, and the Company's pay equity.
We are also committed to ensuring our recruitment process is accessible to all applicants.
If you need a reasonable accommodation during the application or interview process, please contact us at careers@mediaradar.
com . We’re excited to meet people who share our values and want to build the future with us.
Responsibilities Design and execute risk-based audit and sampling programs across classification, reference data, and governed datasets.
Test outputs against authored rules, definitions, and quality thresholds, documenting pass/fail evidence.
Quantify quality across dimensions (accuracy, completeness, consistency, timeliness) and track trends over time.
Validate the effectiveness of human-in-the-loop review, identifying where validation is or is not catching errors.
Investigate root causes of quality issues and recommend rule, process, or training improvements.
Produce clear audit findings, scorecards, and assurance reporting for governance and leadership.
Maintain audit trails and evidence sufficient to support internal and external scrutiny.
Partner with Governance to refine rules and thresholds based on observed failure patterns.
Success in this role will be measured by: Assurance Coverage – Defined, risk-based audit coverage across critical datasets and classification outputs.
Quality Visibility – Reliable, repeatable measurement of quality against thresholds, with clear trends.
Issue Detection – Early identification of systemic quality issues before they reach downstream consumers.
Validation Effectiveness – Evidence that human validation is catching the errors it is meant to catch.
Actionability – Findings that lead to concrete rule, process, or training improvements.
Trust – Leadership confidence in an objective, evidence-based view of data quality.
Key Qualifications and Role Requirements 3–6 years in data quality, audit, data governance, analytics, or a closely related field.
Experience designing sampling or audit methodologies and measuring quality objectively.
Strong analytical skills and fluency with spreadsheets, SQL, or data analysis tooling.
Ability to test outputs against rules and standards and document evidence clearly.
Sound judgment and the independence to report findings objectively.
Familiarity with data quality dimensions and assurance practices.
Exposure to AI/ML-assisted classification and human-in-the-loop workflows a plus.
DAMA / DMBOK familiarity a plus.
Excellent written and verbal communication skills.
