Direct Client - Decision Scientist

This Decision Scientist will partner with Digital Product Managers, Engineering, UX, and Operations to drive data-informed product decisions across Product Ordering experiences. This role will leverage advanced analytics, experimentation, AI-enabled insights, and business performance analysis to help improve customer experience, operational efficiency, and product outcomes., * Analyze product, operational, and customer experience performance to identify trends, root causes, opportunities, and risks.

• Develop actionable recommendations that influence product prioritization, roadmap decisions, and feature optimization.
• Anticipate stakeholder questions and proactively provide insights that support effective decision-making.
• Monitor and communicate performance against key business, customer, and operational KPIs.

Strategic Analytics & Decision Support

• Build models, analyses, forecasts, and scenario planning tools that inform strategic prioritization and investment decisions.
• Partner with Product Managers to quantify business impact, define success metrics, and measure return on investment for product initiatives.
• Support roadmap planning by assessing tradeoffs, sizing opportunities, and evaluating expected outcomes.

Experimentation & Product Measurement

• Define measurement strategies for new products and capabilities.
• Design and evaluate A/B tests, pilots, and experiments to validate hypotheses and guide product decisions.
• Establish product health, adoption, engagement, and operational success metrics.
• Create standardized measurement frameworks that can be applied consistently across products and channels.

Data Products, Dashboards & AI Enablement

• Build scalable dashboards, AI-powered tools, and self-service analytics capabilities that enable Product Managers to independently assess product performance.
• Identify opportunities to automate recurring analyses and reporting.
• Partner with data engineering and analytics teams to improve data quality, accessibility, and reporting capabilities.
• Drive enhancements to existing dashboards and data products based on evolving business needs.

Business Problem Solving

• Lead cross-functional teams through complex and ambiguous business questions: defining key problems and opportunities, developing analytical hypotheses, designing research and measurement approaches, and synthesizing results into actionable recommendations.
• Conduct inquiry-driven analysis to uncover emerging customer, operational, and business insights.

Executive Communication & Storytelling

• Develop concise, executive-ready narratives that communicate business performance, product outcomes, risks, and recommendations.
• Present findings and strategic insights to product leadership and senior executives.
• Translate technical analyses into clear business implications and recommended actions.

Thought Leadership

• Act as a trusted analytics partner across Ordering and broader Digital Product teams.
• Promote best practices in product measurement, experimentation, decision science, and AI-enabled analytics.
• Bring an outside-in perspective on emerging analytics techniques, product measurement frameworks, and decision-support capabilities.

A Day in This Role Product Analytics & Monitoring

• Build and maintain product health scorecards and performance dashboards.
• Create automated reporting and monitoring solutions.
• Conduct recurring business reviews for product leaders.

AI & Self-Service Analytics

• Build AI-enabled tools that allow Product Managers to self-service product performance questions, explore trends and anomalies, access KPI reporting, and generate insights and recommendations.

Product Measurement & Experimentation

• Establish success criteria for new features and experiences.
• Measure feature adoption, conversion, efficiency improvements, and customer outcomes.
• Evaluate pilot performance and develop scaling recommendations.

Strategic Analysis

• Customer behavior analysis
• Operational efficiency analysis
• Forecasting and scenario planning
• Investment prioritization support

The ideal candidate combines strong analytical capabilities with business acumen and the ability to translate complex data into actionable recommendations for product and business leaders. Required Skills & Background

• Experience with Azure: data lake storage, SQL Server, and legacy systems
• Experience with Oracle; performing exploratory data analysis and cleansing, massaging, and aggregating data
• Proficiency in Excel, SQL, SAS, R, Python, Tableau/Power BI, and experimental design platforms
• Working knowledge of business processes and strong general business acumen
• Experience providing analytic support (code documentation, data transformations, algorithms, etc.)
• Ability to procure and manipulate large-scale, complex data from a variety of systems (AWS, Azure, Oracle, on-prem, web tools, etc.)
• Ability to effectively present complex technical material to non-technical audiences in an approachable way

Technology Used

• Microsoft Office Suite
• Smartsheet

Nice to Have

• Databricks experience

Top Skills

• Strategic Analytics & Decision Support (4+ years) - translating complex data into actionable recommendations for product and business leaders
• Communication (5+ years)
• Attention to Detail (5+ years), * Bachelor’s degree in a relevant field preferred

Additional Required Skills

• Ability to translate complex business problems into practical data and technical solutions.
• Experience creating and implementing data-driven workflows.
• Experience working with data dictionaries, data definitions, and data documentation.
• Experience working with data engines / data platforms and structuring data for analytics.
• Strong ability to gather and translate business requirements into data solutions.
• Experience collaborating across business and technical teams to understand requirements, structure data, and develop solutions.
• Ability to connect business objectives with data, analytics, and technical solutions.
• Experience designing data transformations, analytical processes, and workflows that support business decision-making.

Preferred / Nice-to-Have

• Experience with AI-enabled analytics or generative AI.
• Experience with Microsoft Copilot or similar AI productivity tools.
• Experience supporting AI adoption or enabling non-technical users through AI/self-service solutions.

Description: About Weyerhaeuser At Weyerhaeuser, we are the world’s premier timberland, and forest products company. Sustainability is the founding concept of our business, and …