ML Data Quality Lead

ML Data Quality Lead – United Kingdom Fully remote working Duration 2 Months Day rate – Outside IR35 upto £650 A leading client in Manchester is hiring an ML Data Quality Lead to run a sprint-based program, with most technical tasks front-loaded. The role fills a key gap, overseeing data quality, validation, and model input integrity for a complex machine learning pipeline under tight deadlines. Key duties include managing the end-to-end data and model validation process—from raw data ingestion through output auditing. Tasks cover adversarial test design, feature normalization, data quarantine, privacy-preserving ML, and ensuring model decisions are auditable. Key skills and responsibilities, • Practical experience in designing and running adversarial test suites for machine learning models in both production and near-production settings. • Skilled in applied ML data engineering, including feature normalization, building data validation pipelines, and implementing scalable quality rules. • Knowledge of privacy-preserving machine learning techniques such as data minimization, managing consent, and understanding differential privacy concepts. • Experienced in defining ML output formats that can be audited, as well as setting up structured logging to track model decisions. • Acquainted with data governance standards, including crafting retention policies, meeting data residency obligations, and designing tenancy models. • Proven ability to deliver results in high-pressure program launches, as opposed to only working on standard project-based assignments. Interested? Please submit your updated CV to Dean Sadler-Parkes at Harvey Nash for immediate consideration.