Industrial Data Scientist: ML for Smart Manufacturing

Weyerhaeuser; Seattle (WA); On-site; USD 109,000 - 163,000; Full time

Benefits offered by this job

Annual bonus

401k plan

Paid vacation

Health benefits

Professional development

Job summary

Weyerhaeuser is seeking a Data Scientist to apply machine learning to manufacturing, reliability, and supply chain problems. You will work with historian data, MES, and sensor streams to improve product quality and mill uptime.

You will lead model development, experiments, and deployment, collaborating with IT and operations teams to translate complex business needs into scientific approaches and measurable improvements.

Qualifications

• 5+ years of experience developing and deploying machine learning solutions in manufacturing, industrial, or related domains.
• Strong software engineering skills in Python and modern ML frameworks.
• Experience with experimentation, causal inference, and visualization tools.

Responsibilities

• Partner with manufacturing, reliability, maintenance, quality, and operations teams to solve business problems with ML.
• Analyze time-series, historian, MES, ERP, and sensor data to identify patterns and root causes.
• Define success metrics balancing model performance with business outcomes.
• Own end-to-end model lifecycle: feature engineering, training, deployment, monitoring, retraining.
• Collaborate with engineers to productionize models and integrate AI into workflows.
• Develop dashboards and visualizations to drive data-driven decisions.

Skills

Python

Machine Learning

Statistics

Experimentation

A/B testing

Causal inference

Data visualization

Cloud platforms

Education

Bachelor's or Master's in a quantitative field

Tools

Power BI

Plotly

Matplotlib

AWS

Azure

Snowflake

MLOps

Job description

Weyerhaeuser is seeking a Data Scientist to apply machine learning to manufacturing, reliability, and supply chain problems. You will work with historian data, MES, and sensor streams to improve product quality and mill uptime.

You will lead model development, experiments, and deployment, collaborating with IT and operations teams to translate complex business needs into scientific approaches and measurable improvements.