Top Remote Data & Analytics Jobs in Omaha, NE

The Analytics & Google Tag Manager Specialist is responsible for migrating clients from Google Analytics 3 to Google Analytics 4, setting up GA4 and GTM, and linking accounts to Google Ads.

The Senior Product Analyst will oversee product analytics projects, collaborating with teams to develop KPIs, conduct A/B testing, and provide data-driven insights to enhance decision-making.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

The Senior Data Analyst will conduct quantitative analysis, optimize products through data insights, and lead A/B testing in collaboration with various stakeholders.

The Senior Systems Analyst will enhance data exchanges, support project deployments, analyze data strategies, and solve complex problems within the Consumer Markets Division.

The Senior Manager, Analytics & Insights will support sales and operational teams through advanced analytics and data-driven insights, focusing on GTM strategies and analytics infrastructure.

As a Data Science Intern, you'll learn to translate business challenges into statistical problems, analyze large datasets, build machine learning models, and communicate insights effectively.

The Senior Analyst in Revenue Operations will manage planning cycles, headcount, performance plans, financial modeling, and collaborate with FP&A to support the GTM organization.

The Analytics Implementation Manager will lead the implementation and validation of analytics infrastructure, ensuring measurement accuracy and reliability across client accounts. Responsibilities include deploying tagging solutions, managing data layers, coding in JavaScript, and collaborating with cross-functional teams to troubleshoot and enhance performance tracking.

Lead design and expansion of a unified analytics data platform integrating Medicare claims, clinical systems, and vendor feeds. Implement AI-augmented data engineering (LLM coding assistants, automated QA, autonomous data-quality agents), build validation/reconciliation/audit infrastructure, partner with analytics teams for reporting and modeling needs, and drive large-scale analytics platform and web app implementation while collaborating with IT on security and deployment standards.