Top Remote Data & Analytics Jobs

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

As an Analytics Manager in Growth, you'll lead reporting and insights on customer activation, conduct analyses to optimize customer experiences, collaborate with teams for key metrics, and manage growth initiatives.

The Data Analyst will analyze extensive datasets to identify behavioral patterns, create analytics, and collaborate on data projects with product managers and developers.

The Reltio MDM Solutions Lead designs and implements MDM solutions, analyzes business requirements, and collaborates with teams to enhance data management and analytics.

The Senior Associate monitors UW automation performance, analyzes data, generates insights to improve automation, collaborates with cross-functional teams, and develops reporting tools for underwriting.

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.

Design, develop, and secure database systems that integrate structured and unstructured data from diverse sources. Build ETL processes, SQL/PLSQL/T-SQL routines, Oracle APEX web apps, and Power BI reporting to enable data mining, quality checks, and analytics for engineering and materials data.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

The Director of Privacy Design and Governance ensures privacy compliance within product development, advancing a comprehensive program aligned with regulations while providing guidance on data handling, risks, and privacy rights.

Build and deliver end-to-end, production-grade data solutions: design and maintain scalable ETL pipelines, ingest from diverse sources, implement dbt transformations, ensure data quality and observability, optimize performance and cost, and partner with analytics, product, and engineering teams to drive business impact.