Top Remote Machine Learning Jobs in Portland, OR

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

As a Compliance Data Scientist Co-op, you will automate data processing, enhance Power BI reports, and utilize AI for compliance improvements.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.