Top Senior Level Data & Analytics Jobs in Portland, OR

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.

The AI/ML Data Analyst will develop mathematical models and algorithms for the AI/ML initiative, analyze data models, review algorithms for performance, and troubleshoot field issues. They will also serve as a subject matter expert on AI tools and techniques, ensuring all business activities align with company policies.

In this role, the Senior Manager of Data Engineering will lead and expand a team of engineers, design data strategy and architecture, and collaborate with technical leaders to enhance data infrastructure and support business growth.

As a Senior Data Scientist for JD Power, you'll lead complex data science projects, focusing on feature engineering and model building. You will leverage advanced AI/ML techniques and tools like SQL, Python, and AWS SageMaker to extract insights and impact products in the automotive industry. Your role will also involve collaborating with teams to develop analytics for new products and creating visual reports for clients.

The Application Data Architect will guide software engineering teams in database design, optimizing data for online applications, and ensuring data integrity and security. Responsibilities include collaborating with various teams to translate requirements into database designs, managing data catalogs, and improving data architecture best practices.