Top Remote Data & Analytics Jobs in Kansas City, MO

Lead marketing analytics to measure and optimize full-funnel performance. Build dashboards, analyze paid media and web funnels, assess lead quality and conversion, advise on budget allocation, support executive reporting, and improve analytics infrastructure across Marketing, Finance, and RevOps.

The role involves supporting sales and services initiatives through data analysis, relationship management, and cross-functional collaboration to inform strategies and optimize processes.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

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.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

Lead discovery and requirements for a workforce development SaaS platform, translate needs into user stories, and manage UAT delivery.

The Data Engineer role involves designing and maintaining AWS-cloud-native data systems, developing ETL processes, optimizing data pipelines, and ensuring data security and governance in healthcare data applications.

As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize workflows with dbt and Snowflake, and mentor teams across functions to enhance data reliability and performance.