Top Data & Analytics Jobs in Charlotte, NC

As a KYC Quality Assurance Tester, you will ensure the quality and compliance of KYC processes, review records, and provide feedback to stakeholders.

Design, develop, test, and support scalable batch and real-time data pipelines. Partner across teams to define requirements, implement data governance, automate monitoring, troubleshoot performance, and mentor peers while productionalizing big data solutions on cloud platforms.

The VP of Data & Insights leads GitLab's data strategy, overseeing a team to enhance analytics capabilities and drive AI integration across the enterprise.

Lead the development and execution of data-driven marketing analytics strategies, optimizing client customer acquisition through actionable insights and advanced analytics techniques.

Lead design and build of a new graph-backed enterprise data platform: architect graph and relational storage, ingestion and ETL/ELT pipelines, entity resolution, temporal models, governance, APIs, and production deployments across cloud and customer-hosted environments.

The Marketing Data Analyst will support marketing performance evaluation, optimize initiatives, manage data processing, and create reports for stakeholders.

The Business Analyst will support partnership growth by building analytics infrastructure, addressing data quality issues, and providing insights for strategic decision-making.

The Senior Catastrophe Analyst will develop automated processes, design databases, create pricing tools, and provide analytics to drive catastrophe risk management.

Support a defined book of business by validating, transforming, and reconciling data to ensure regulatory compliance for conversion and portability notifications. Manage daily processing, audits, file onboarding, reporting outputs, and liaise with stakeholders to resolve discrepancies and drive process improvements.

Manage a team of data scientists to develop and validate statistical and machine learning models, leveraging large data sets to drive business decisions and ensure model effectiveness within the credit review context.