Top Remote Analysis Reporting Jobs in Charleston, SC

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

The Analyst I will own analytics workflows, drive improvements, build data models, and support business metrics while collaborating across teams.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Build and lead the Compliance data function, owning data products for Customer Risk, Transaction Monitoring, AML, Sanctions. Design and implement data risk frameworks (quality, usage, lineage), enforce data contracts between producers and consumers, maintain end-to-end lineage with Engineering, and drive a risk-based data roadmap aligned with compliance requirements.

Lead development and continuous improvement of EHS safety management systems and DriveSafe program. Oversee driver scorecards, performance analytics, dashboards, and ad hoc reporting. Partner with EHS, operations, IT, and leadership to align systems, ensure data governance, drive projects, implement EHS technologies, train users, support compliance, and use data-driven insights to reduce incidents and improve safety outcomes.

As a Healthcare Analyst II, you will analyze healthcare data to optimize strategies, conduct quantitative analysis, and provide insights for clinical interventions, partnering with cross-functional teams.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Lead company-wide data governance and standards, enforce data contracts and schema/version control, manage PII/RBAC and master data, establish data-quality metrics and monitoring, grow and run the governance team, remain hands-on with data profiling and SQL, and use AI to accelerate governance work and modeling.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.