Principal Data Scientist

About the role

We are seeking an experienced Principal Data Scientist to provide technical leadership and apply data science to solve complex business problems across manufacturing, operations reliability, supply chain, and product quality domains.

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.

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.

Job Information

• Technology Primary Location: USA-WA-Seattle
• Schedule: Full-time
• Job Level: Individual Contributor
• Job Type: Experienced
• Shift: Day (1st)
• Relocation Assistance Available: 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.
• Preferred, Not Required: 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.
• 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.