Data Analyst II

Job Description Are you passionate about transforming complex data into meaningful insights that drive better decisions? Would you like to work with innovative data solutions that help shape the future of insurance ris k? About the Business LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle, all while reducing risk. You can learn more about LexisNexis Risk at https://risk.lexisnexis.com/insurance. 1 About our Team The Data Engineering Team in the UK&I features 20 individuals but sits within a global Data Engineering team of over 400+ individuals. Data Management is currently a team of 2.5 team members but is expanding as out product offerings grow within the UK. About the Role In this role, you will analyse and interpret complex data to support business decisions and improve data quality across the insurance lifecycle. You’ll collaborate with a variety of stakeholders to deliver insights, resolve issues, and contribute to continuous improvement initiatives. This is an opportunity to combine analytical expertise with modern tools to drive efficiency and innovation. Responsibilities Analyse data to support business decisions and clearly communicate findings Collaborate with customers, data providers, and internal stakeholders to gather requirements and resolve issues Perform data validation, profiling, reconciliation, and quality assessments Investigate and resolve data issues using root-cause analysis and track remediation actions Develop and modify queries (e.g., SQL) to support research and data quality checks Present insights to both technical and non-technical audiences Support data onboarding, workflow improvements, and operational efficiency initiatives (including automation/AI use) Identify process inefficiencies and contribute to optimisation, risk management, and change initiatives Requirements 3+ years’ experience in data management, analysis, or customer-facing data roles Strong analytical skills with experience handling large or complex datasets Advanced SQL and Power BI reporting capabilities Knowledge of data lifecycle processes (profiling, validation, reconciliation) Experience with root-cause analysis and data quality improvement Strong communication and stakeholder engagement skills Exposure to APIs, data integration formats, and modern data platforms (e.g., Azure) preferred Experience using AI/automation tools to enhance analysis and efficiency, with a proactive and detail-oriented mindset 



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