Principal Data Scientist

About Weyerhaeuser
At Weyerhaeuser, we are the world’s premier timberland, and forest products company. Sustainability is the founding concept of our business, and our values drive every decision to ensure we continue to lead the forestry industry in sustainability practices. And we know about sustainability – we led it in the forestry industry when we planted our first seedling by hand in 1938. We recognize that our success is dependent on the success of our people. For over 125 years, our Weyerhaeuser team has been making a difference in the world – from the seedlings we plant, to the forests and trees we nurture, we ensure every acre is managed with diligence, patience and pride. That’s the Weyerhaeuser way.

About the Role
Grasp the opportunity to apply data science to the physical world of manufacturing! We are seeking an experienced Principal Data Scientist to provide technical leadership and passionate about applying machine learning, statistics, experimentation, and optimization techniques to solve complex business problems across manufacturing, operations reliability, supply chain, and product quality domains. We have a large manufacturing presence in North America with lumber, OSB, plywood, and engineered lumber products mills in Canada and the United States. Our Weyerhaeuser brand and scale of operations make us a major player in the wood products business. You would be partnering with our manufacturing mills to identify, analyze, and solve complex problems related to production quality, equipment reliability, and preventative maintenance. Your work would directly impact operational efficiency, improved product quality, and mill uptime. This role is responsible for shaping AI and ML strategy, defining reusable machine learning capabilities, leading complex experimentation, and delivering scalable solutions that create measurable business value. You have a high attention to detail, but are good at seeing the big picture, and aren’t afraid to think outside the box, and champion your ideas. You have experience articulating opportunity, as well as creating and successfully managing projects. You are effective at communicating timely and relevant information to business leaders and internal partners.

Responsibilities

• Lead the design of scalable solutions across multiple business domains.

• Establish reusable patterns, standards, and best practices for model development and deployment.

• Lead and develop advanced machine learning, optimization, forecasting, generative AI, and decision intelligence solutions. 

• Define success metrics that balance model performance with business outcomes including revenue growth, operational efficiency, customer experience, safety, and risk reduction. 

• Partner with Product Managers and Operation teams to identify, prioritize, and frame business opportunities that can be solved with scientific framework. 

• Influence technical direction across multiple programs without direct authority. 

• Design, execute, and analyze online and offline experiments, including A/B testing, causal inference, and counterfactual analysis, to evaluate the impact of data science solutions on business outcomes. 

• Design, develop, and evaluate machine learning and deep learning models to solve forecasting, optimization, reliability, anomaly detection, and decision-support problems. 

• Design and implement statistical process control methods and anomaly detection techniques to proactively address quality issues in the manufacturing process. 

• Own the end-to-end model lifecycle, including feature engineering, training, validation, deployment, monitoring, retraining, and continuous improvement. 

• Establish standards for feature stores, model registries, inference services, observability, and governance. 

• Collaborate with software engineers, ML engineers, and data engineers to productionize models and integrate AI capabilities into business workflows. 

• Demonstrate the ability to apply data science and machine learning techniques across multiple domains (e.g., manufacturing, supply chain, pricing, logistics), abstracting core patterns, and adapting solutions to new problem spaces. 

• Translate ambiguous business problems into scientific approaches and influence stakeholders through data-driven recommendations. 

• Develop analytical visualizations and communicate findings through dashboards, notebooks, and presentations that drive business decisions. 

• Mentor junior team members and contribute to data science standards, reusable patterns, and best practices. 

About Weyerhaeuser
At Weyerhaeuser, we are the world’s premier timberland, and forest products company. Sustainability is the founding concept of our business, and our values drive every decision to ensure we continue to lead the forestry industry in sustainability practices. And we know about sustainability – we led it in the forestry industry when we planted our first seedling by hand in 1938. We recognize that our success is dependent on the success of our people. For over 125 years, our Weyerhaeuser team has been making a difference in the world – from the seedlings we plant, to the forests and trees we nurture, we ensure every acre is managed with diligence, patience and pride. That’s the Weyerhaeuser way.

About the Role
Grasp the opportunity to apply data science to the physical world of manufacturing! We are seeking an experienced Principal Data Scientist to provide technical leadership and passionate about applying machine learning, statistics, experimentation, and optimization techniques to solve complex business problems across manufacturing, operations reliability, supply chain, and product quality domains. We have a large manufacturing presence in North America with lumber, OSB, plywood, and engineered lumber products mills in Canada and the United States. Our Weyerhaeuser brand and scale of operations make us a major player in the wood products business. You would be partnering with our manufacturing mills to identify, analyze, and solve complex problems related to production quality, equipment reliability, and preventative maintenance. Your work would directly impact operational efficiency, improved product quality, and mill uptime. This role is responsible for shaping AI and ML strategy, defining reusable machine learning capabilities, leading complex experimentation, and delivering scalable solutions that create measurable business value. You have a high attention to detail, but are good at seeing the big picture, and aren’t afraid to think outside the box, and champion your ideas. You have experience articulating opportunity, as well as creating and successfully managing projects. You are effective at communicating timely and relevant information to business leaders and internal partners.

Responsibilities

• Lead the design of scalable solutions across multiple business domains.

• Establish reusable patterns, standards, and best practices for model development and deployment.

• Lead and develop advanced machine learning, optimization, forecasting, generative AI, and decision intelligence solutions. 

• Define success metrics that balance model performance with business outcomes including revenue growth, operational efficiency, customer experience, safety, and risk reduction. 

• Partner with Product Managers and Operation teams to identify, prioritize, and frame business opportunities that can be solved with scientific framework. 

• Influence technical direction across multiple programs without direct authority. 

• Design, execute, and analyze online and offline experiments, including A/B testing, causal inference, and counterfactual analysis, to evaluate the impact of data science solutions on business outcomes. 

• Design, develop, and evaluate machine learning and deep learning models to solve forecasting, optimization, reliability, anomaly detection, and decision-support problems. 

• Design and implement statistical process control methods and anomaly detection techniques to proactively address quality issues in the manufacturing process. 

• Own the end-to-end model lifecycle, including feature engineering, training, validation, deployment, monitoring, retraining, and continuous improvement. 

• Establish standards for feature stores, model registries, inference services, observability, and governance. 

• Collaborate with software engineers, ML engineers, and data engineers to productionize models and integrate AI capabilities into business workflows. 

• Demonstrate the ability to apply data science and machine learning techniques across multiple domains (e.g., manufacturing, supply chain, pricing, logistics), abstracting core patterns, and adapting solutions to new problem spaces. 

• Translate ambiguous business problems into scientific approaches and influence stakeholders through data-driven recommendations. 

• Develop analytical visualizations and communicate findings through dashboards, notebooks, and presentations that drive business decisions. 

• Mentor junior team members and contribute to data science standards, reusable patterns, and best practices. 

• 10+ years of experience developing and deploying machine learning and AI solutions. 

• Strong software engineering skills in Python and modern ML frameworks. 

• Deep expertise in supervised learing, forecasting, optimization, statistical modeling, anomaly detection, model evaluation and experimentation methodologies. 

• Demonstrated success delivering enterprise-scale AI products from concept through production. 

• Experience leading highly ambiguous technical initiatives. 

• Proven ability to influence technical strategy across multiple teams and organizations. 

• Experience with experimentation and causal inference methods, including A/B testing, quasi-experimental designs, and counterfactual analysis. 

• Experience communicating insights using Power BI or Python-based visualization libraries such as Plotly and Matplotlib. 

• Experience with modern cloud platforms and data architectures, including AWS, Azure, Snowflake, and MLOps, CI/CD, and model lifecycle management. 

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 

Education 

• PhD in Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or related quantitative discipline; or Master’s degree with equivalent industry experience. 

What We Offer\: 

Compensation\: This role is eligible for our annual merit-increase program, and we are targeting a salary range of $131,082-196,766 based on your level of skills, qualifications and experience. You will also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 15% of base pay. Potential plan funding may range from zero to two times that target. 

Benefits\: When you join our team, you and your dependents will be offered coverage under our comprehensive employee benefits plan, which includes medical, dental, vision, short and long-term disability, and life insurance. We offer a pre-tax Health Savings Account option which includes a company contribution. Other benefit options are also available such as voluntary Long-Term Care and Employee Assistance Programs. We also support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities to help you chart your path to a fulfilling career.

Retirement\: Employees are able to enroll in our company’s 401k plan, which includes a paid company match in addition to our contribution equal to 5% of your eligible pay.

Paid Time Off or Vacation\: We provide eligible employees who are scheduled to work 25 hours or more per week with 3-weeks of paid vacation to use during your first year of employment. In addition, after being employed for six months, eligible employees begin to accrue vacation for future use. We also recognize eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees. 

Weyerhaeuser is an equal opportunity employer. Inclusion is one of our five core values and we strive to maintain a culture where all our people feel a sense of belonging, opportunity and shared purpose. We are committed to recruiting a diverse workforce and supporting an equitable and inclusive environment that inspires people of all backgrounds to join, stay and thrive with our team.

#salary

• 10+ years of experience developing and deploying machine learning and AI solutions. 

• Strong software engineering skills in Python and modern ML frameworks. 

• Deep expertise in supervised learing, forecasting, optimization, statistical modeling, anomaly detection, model evaluation and experimentation methodologies. 

• Demonstrated success delivering enterprise-scale AI products from concept through production. 

• Experience leading highly ambiguous technical initiatives. 

• Proven ability to influence technical strategy across multiple teams and organizations. 

• Experience with experimentation and causal inference methods, including A/B testing, quasi-experimental designs, and counterfactual analysis. 

• Experience communicating insights using Power BI or Python-based visualization libraries such as Plotly and Matplotlib. 

• Experience with modern cloud platforms and data architectures, including AWS, Azure, Snowflake, and MLOps, CI/CD, and model lifecycle management. 

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 

Education 

• PhD in Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or related quantitative discipline; or Master’s degree with equivalent industry experience. 

What We Offer\: 

Compensation\: This role is eligible for our annual merit-increase program, and we are targeting a salary range of $131,082-196,766 based on your level of skills, qualifications and experience. You will also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 15% of base pay. Potential plan funding may range from zero to two times that target. 

Benefits\: When you join our team, you and your dependents will be offered coverage under our comprehensive employee benefits plan, which includes medical, dental, vision, short and long-term disability, and life insurance. We offer a pre-tax Health Savings Account option which includes a company contribution. Other benefit options are also available such as voluntary Long-Term Care and Employee Assistance Programs. We also support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities to help you chart your path to a fulfilling career.

Retirement\: Employees are able to enroll in our company’s 401k plan, which includes a paid company match in addition to our contribution equal to 5% of your eligible pay.

Paid Time Off or Vacation\: We provide eligible employees who are scheduled to work 25 hours or more per week with 3-weeks of paid vacation to use during your first year of employment. In addition, after being employed for six months, eligible employees begin to accrue vacation for future use. We also recognize eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees. 

Weyerhaeuser is an equal opportunity employer. Inclusion is one of our five core values and we strive to maintain a culture where all our people feel a sense of belonging, opportunity and shared purpose. We are committed to recruiting a diverse workforce and supporting an equitable and inclusive environment that inspires people of all backgrounds to join, stay and thrive with our team.

#salary