The Data Quality Check Specialist role supports the development of AI models and the integrity of Company & People Databases through rigorous quality assessments. Work involves evaluating AI-generated outputs and validating large data sets to ensure accuracy, consistency, and adherence to quality standards. Accountabilities: + AI/Machine Learning Output Quality + Involved in the development of machine learning (ML) and artificial intelligence (AI) models by leveraging language mastery and subject area expertise. Individuals in this role will be responsible for performing quality assessments of GenAI outputs such as document summaries, search results, AI chat responses, and draft reports focused on company research use cases + Understand and identify GenAI hallucinations via human testing and validation + Company Data Quality + Involved in the quality assessment of our Company & People Databases by regularly scoring large data sets. Individuals in this role will have to pay intensive attention to scoring rules and methods to ensure we have solid quality numbers overtime. There may be additional Company & People data reviews focused on specific sources, specific companies. + Perform quality assessment checks of company and personnel data from Excel. + Implement and maintain rigorous quality control measures within the QA team to uphold data integrity standards. Qualifications: + Must possess a bachelor’s degree in any field + Good expertise with Excel and shared files + Ability to become familiar with other software tools, such as Prodigy and Azure Dev Ops + Subject Area Expertise + Company research use cases including, but not limited to, Corporate Development, Sales Intelligence/Business Development, Competitive Intelligence and Market Intelligence. This is important to ensure the AI/ML model is biased correctly to the targeted customer persona(s). + Strong knowledge of business/company information (company financials, public filings, company press releases, earnings calls, ESG ratings etc) and places to get this information. + Attention to detail – A strong attention to detail is needed in this role – completeness/accuracy of data labelling/annotation is important to the successful development/testing of models. + Adaptability – Individuals in this role need to be comfortable with change as this field is changing rapidly. + Language mastery: English minimum LexisNexis, a division of RELX, is an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120. Please read our Candidate Privacy Policy (https://www.relx.com/careers/join-us/privacy) . RELX is a global provider of information-based analytics and decision tools for professional and business customers, enabling them to make better decisions, get better results and be more productive. Our purpose is to benefit society by developing products that help researchers advance scientific knowledge; doctors and nurses improve the lives of patients; lawyers promote the rule of law and achieve justice and fair results for their clients; businesses and governments prevent fraud; consumers access financial services and get fair prices on insurance; and customers learn about markets and complete transactions. Our purpose guides our actions beyond the products that we develop. It defines us as a company. Every day across RELX our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate.