Data Scientist

Weyerhaeuser is hiring an experienced Data Scientist onsite in Seattle to apply machine learning, statistics, experimentation, and optimization to industrial and operations reliability problems.

Responsibilities

• Partner with manufacturing, reliability, maintenance, quality, and operations teams to translate business problems into machine learning opportunities.
• Analyze large volumes of industrial data including time-series, historian, MES, ERP, and sensor feeds to detect patterns, bottlenecks, and root causes.
• Create reusable patterns, standards, and best practices for model development and deployment.
• Define success metrics that balance model performance with business outcomes across revenue growth, operational efficiency, customer experience, safety, and risk reduction.
• Work with Product Managers and operations teams to identify, prioritize, and frame opportunities solvable through scientific methods.
• Provide technical influence across multiple programs without direct authority.
• Design, run, and evaluate online and offline experiments, including A/B testing, causal inference, and counterfactual analysis.
• Develop and assess machine learning and deep learning models for forecasting, optimization, reliability, anomaly detection, and decision support.
• Implement statistical process control and proactive anomaly detection methods to address quality issues in manufacturing.
• Own the end-to-end model lifecycle: feature engineering, training, validation, deployment, monitoring, retraining, and continuous improvement.
• Collaborate with software engineers, ML engineers, and data engineers to productionize models and integrate AI into business workflows.
• Translate ambiguous problems into scientific approaches and communicate data-driven recommendations.
• Build analytical visualizations and communicate findings through dashboards, notebooks, and presentations.
• Contribute to reusable analytics libraries, feature engineering patterns, and best practices across Industrial AI use cases.

Requirements

• 5+ years of experience developing and deploying machine learning and AI solutions in manufacturing, industrial, supply chain, or related domains.
• Strong software engineering skills in Python and modern ML frameworks.
• Expertise in supervised learning, forecasting, optimization, statistical modeling, anomaly detection, model evaluation, and experimentation methodologies.
• Proven success delivering enterprise-scale AI products from concept through production.
• Experience leading highly ambiguous technical initiatives.
• Ability to influence technical strategy across multiple teams and organizations.
• Experience with experimentation and causal inference, including A/B testing, quasi-experimental designs, and counterfactual analysis.
• Experience communicating insights using Power BI or Python visualization libraries such as Plotly and Matplotlib.
• Experience with modern cloud platforms and data architectures, including AWS, Azure, Snowflake, plus MLOps, CI/CD, and model lifecycle management.

Technologies

• Python
• Power BI
• Plotly
• Matplotlib
• AWS
• Azure
• Snowflake
• MLOps
• CI/CD
• MES
• ERP

Benefits

• Medical, dental, vision, short and long-term disability, and life insurance.
• Pre-tax Health Savings Account option with a company contribution.
• Annual Incentive Program cash bonus targeting 15% of base pay.
• Potential plan funding may range from zero to two times that target.
• 401k plan with a paid company match in addition to a company contribution equal to 5% of eligible pay.
• 3-weeks of paid vacation during the first year for eligible employees scheduled to work 25 hours or more per week.
• Vacation accrual begins after being employed for six months.
• Eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees.
• Support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities.

Preferred, Not Required

• Practical experience with Recommendation Systems, Pricing Optimization, and Computer Vision.
• Practical experience in Forestry Services or Wood Product manufacturing.
• Experience with Industrial Internet of Things and time-series manufacturing data.

Role Details

• Compensation: USD 98,811 - 148,217 per year (salary range based on level of skills, qualifications, and experience).
• Location: Seattle, WA 98104 (onsite).
• Schedule: Full-time.
• Job level: Individual Contributor.
• Job type: Experienced.
• Shift: Day (1st).