Top Remote Senior Level Data & Analytics Jobs in Portland, OR

Lead the Data Science team, developing AI models and statistical systems while collaborating with cross-functional teams. Drive research and data strategies that enhance product effectiveness and farmer profitability.

The Senior Data Analyst will predict revenue and margins to guide marketing and sales decisions, providing actionable insights and solutions to improve business decisions. This role involves analyzing data, maintaining performance reports and dashboards, and collaborating with various teams to drive data-driven strategies.

The User Acceptance Testing Analyst is responsible for performing UAT for system upgrades and releases. This role involves creating and reviewing test cases, developing testing strategies, and maintaining documentation. The analyst will conduct defect tracking, manage test data, and establish relationships with business partners while identifying risks and improving the UAT process.

The Senior IMS Mainframe DBA will create, maintain, design, and troubleshoot client databases, focusing on IMS environments. Responsibilities include database software upgrades, daily maintenance, backups, monitoring, performance optimization, and on-call support. They will collaborate with vendors and develop best practices for database management, ensuring security and efficiency.

As a Principal Data Scientist at Appspace, you will analyze data generated by our platform to create valuable reporting and analytics for customers. This includes developing data models, dashboards, and providing user training while collaborating with cross-functional teams to meet customer needs.

As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, work collaboratively with engineers, engage with clients, and mentor project teams, focusing on practical AI solutions for clients.

The Senior Data Engineer will design, develop, and maintain data pipelines and infrastructure, focusing on data needs for AI/ML models. Responsibilities include setting data infrastructure strategy, implementing data transformation processes, ensuring data quality, building data structures, and collaborating with cross-functional teams.