Top Data Management Jobs in Greensboro, NC

Manage a team of ~7 data scientists to deliver experimental design, product analytics, and actionable insights. Partner with product, engineering, and research to build measurement, data products, and reporting; ensure data accuracy, timely delivery, and best practices.

Lead a team of ~7 data scientists to deliver accurate product analytics and experimentation insights. Manage people, mentor staff, partner with product and engineering to build accessible data products, and improve measurement, reporting, and experiment practices to inform product decisions.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights. Manage people, partner with product and engineering, improve measurement and data products, and ensure rigorous large-scale analysis to inform product decisions.

Lead a Product Analytics data science team to deliver timely, accurate insights for product decisions. Manage ~7 data scientists, mentor teammates, partner with product and engineering, develop experimentation and measurement best practices, and build accessible data products and reports.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experiments; support product teams, build accessible data products, mentor staff, and improve measurement and reporting practices.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics: guide experimentation, partner with product and engineering, build accessible data products, mentor staff, and improve measurement and reporting practices to inform product decisions.

Lead a team of product analytics data scientists to deliver timely, accurate quantitative insights for product strategy, experimentation, and measurement. Manage people, mentor staff, partner with product and engineering to build accessible data products, and improve experimentation and reporting practices to inform decisions across the Foundation and movement.

As Senior Manager of IT Commercial Data Management, you will lead data initiatives, manage product ownership, and develop data governance strategies in collaboration with stakeholders, ensuring high data quality and analytics capabilities.

Serve as the primary data partner for Fundraising & Marketing: design and build source-of-truth data models in the lakehouse, create forecasts and donor cohort analyses, automate reporting and data products, support experiment design and ROI measurement, partner with engineering and Salesforce to improve data quality, and translate insights for leadership to drive fundraising strategy.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Manage data engineering efforts to build scalable data infrastructure. Optimize data warehouses, automate reporting, and translate business needs into data solutions.

The role focuses on business analysis and project management, emphasizing analytics and reporting in an Agile environment. Responsibilities include requirements elicitation, solution design, project coordination, and stakeholder engagement to meet business goals in the pharmaceutical sector.

Lead scaling of a commercial channel data management platform for oncology/hematology. Manage vendor and data provider relationships, design data pipelines and governance, improve data quality, oversee data aggregation and provisioning for commercial insights, and ensure compliance, security, and documentation.

The Data Integration Manager leads client data exchange processes, ensuring data quality, managing integration lifecycles, and consulting with clients on data needs, supported by technical expertise in SQL and ETL processes.

The Clinical Data Manager will oversee clinical trial data management activities, ensuring data accuracy, integrity, and compliance with regulatory standards while coordinating with cross-functional teams.

The Data Product Manager will oversee the firmographic data foundation, improving data accuracy, structure, and analytics capabilities to enhance talent acquisition and analytics solutions for clients.

Lead data initiatives, develop machine learning models, conduct analysis to improve programs, and collaborate with cross-functional teams to drive results for health insurance enrollment.

Lead the data management strategy and team to design, build, and maintain scalable ETL pipelines and data infrastructure. Implement data governance, ensure data quality, optimize performance using tools like Airflow, Iceberg, Trino, and Spark, and collaborate with cross-functional teams to make data accessible and actionable.

The Clinical Data Manager oversees clinical trial databases, creates documentation, reviews data, trains staff, and ensures compliance with regulatory standards.

The Senior Clinical Data Manager oversees clinical trial databases, mentors junior staff, and ensures data quality and compliance with regulatory standards.

The Data Product Manager - Curation designs and manages curated data products, overseeing data modeling, governance, and partnership with analytics teams to enhance data usability and support advanced analytics, including Machine Learning.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

The Manager R&D Data Steward oversees data governance, quality management, and stewardship of R&D data, ensuring compliance and integrity across data products and leading a team to support data management initiatives.

The Manager leads business intelligence and data operations, establishes KPI governance, oversees executive reporting, and ensures data-driven decision-making across teams.

As a Senior Manager, R&D Data Steward, you will oversee stewardship of Pharma R&D data, ensuring data quality and compliance across the R&D value chain. You will lead a team, operationalize data governance, and drive improvements in data management processes, leveraging automation and cross-functional collaboration to enhance data-driven insights.