Top Remote Data & Analytics Jobs in Wilmington, NC

As a Memory Developer, you'll record household tasks, shape the robot's memory, and help train its AI for better performance.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

The Senior Korean Linguist manages translation and copy-editing tasks, coordinates with freelancers, and ensures high-quality Korean-language deliverables while improving workflows and supporting quality efforts.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.