Top Remote Data & Analytics Jobs

Zone & Co is seeking a Business Intelligence Engineer with expertise in Power BI, Azure, and SQL. Responsibilities include data modeling, report creation, DAX and SQL scripting, integration, performance tuning, collaboration, and staying up-to-date with the latest BI trends.

Support the design of finance applications, define finance systems strategy, lead User Acceptance Testing, and deliver training on finance tools and technology. Remote-first culture with competitive compensation and benefits.

Seeking a Competitive Intelligence Analyst to support product and sales teams by providing competitive analysis and recommendations for CrowdStrike Falcon Next-Generation SIEM (NG-SIEM). Requires deep technical knowledge in log management, SIEM, and XDR security.

AMP is hiring a Senior Project & Business Development Analyst to support the targeting, pursuit, and execution of innovative, large-scale solid waste projects. This role is remote in the United States and involves identifying high-value opportunities, managing proposal development, and coordinating cross-functional meetings.

Provide technical and analytical support for commercial contracts, manage contract administration, work cross-functionally with various departments to drive profitable growth, and provide training on contract operations and language interpretation.

Lead centralized Data functions for Square including Data Science + Analytics, Machine Learning, and Data Engineering teams. Architect Square's Data strategy, drive data platform roadmap, establish data governance principles, deliver insights, and build top-tier data team.

As a Distinguished Architect at ServiceNow, you will lead AI initiatives with a focus on cutting-edge technologies like deep learning and natural language processing. Responsibilities include collaborating with engineering and product teams, building elegant architectures, architecting reusable components, influencing leadership, performing competitive analysis, and sharing thought leadership at AI conferences.

Lead a team of Data Scientists and Machine Learning Engineers to create AI models that drive company growth. Define strategies, identify use cases, solicit requirements, build accurate models, and teach business teams.

Develop and maintain quote to cash systems and integrations, participate in systems analysis and design, address production issues, communicate status to stakeholders, work on process improvements and automation, collaborate with finance and internal teams for efficiencies, and participate in QA activities.