Top Remote Data & Analytics Jobs in Kansas City, MO

The Business Analyst will collaborate with campus partners to improve business processes, implement data management strategies, ensure compliance, and provide monitoring and training for enterprise applications.

The Staff Data Engineer will architect and implement a next-generation data platform, build data pipelines, and ensure data integrity for actionable insights.

The Senior Analyst will design lead scoring models, automate workflows, and utilize AI tools to derive insights for sales and marketing collaboration. They will also maintain documentation to ensure team efficiency.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

As a Senior Product Analyst, you'll analyze user experience, develop metrics, visualize data, communicate insights, and enhance decision-making for better learning outcomes.

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

The Vice President of Clinical Data & Analytics leads analytics strategy and infrastructure, driving insights to optimize healthcare outcomes and manage costs. They collaborate with executives to enhance clinical programs, improve client reporting, and ensure data-driven decisions. Responsibilities include overseeing data integration, leading HEOR initiatives, and managing a high-performing analytics team.

The Sector Lead for Financial Services will oversee channel research projects, ensuring quality and relevance while guiding a team of analysts. Responsibilities include developing questionnaires, managing research workflows, and expanding coverage across financial services sectors.

Analyze revenue and growth performance, provide insights on auction behavior, measure A/B tests, define KPIs, and perform root-cause analysis.

The Staff Analytics Engineer will enhance the analytics data layer, improve data quality, maintain core data models, and introduce AI-assisted workflows to optimize insights generation.