Job Title: Decision Scientist
Location: 4 days a week on-site (Seattle, WA) - Remote can be considered for candidates with 5+ year exp
Duration: 06 Months
- This Decision Scientist will partner with Digital Product Managers, Engineering, UX, and Operations to drive data-informed product decisions across Coffeehouse 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.
- 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.
Core Responsibilities
Product Performance & Insights
- 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.
- This Decision Scientist will partner with Digital Product Managers, Engineering, UX, and Operations to drive data-informed product decisions across Coffeehouse 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.
- 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.
Core Responsibilities
Product Performance & Insights
- 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 by:
- Defining key problems and opportunities
- Developing analytical hypotheses
- Designing research and measurement approaches
- 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 Coffeehouse 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.
Daily Responsibilities:
- 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
- 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
Interaction level with team:
- Moderate to high based on daily needs
Technology requirements:
- Microsoft Office Suite
- Smartsheet's
Degree or certifications required?:
- Degree in relevant field (BA)
Years experience:
- 4-5+ years of experience, but the more the better, no max limit
Required background skills
- Azure: data lake storage, SQL server and legacy systems
- Oracle; perform exploratory data analysis, cleanse, massage, and aggregate data.
- Proficiency in Excel, SQL, SAS, R, Python, Tableau / PowerBI, and experimental design platforms.
- working knowledge and understanding of business, and business acumen in general
- Provide 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 tool, etc.),
- Effectively presents complex technical material to non-technical audiences in an approachable way.
Nice-to-Haves:
- Data Bricks
- Former client experience
Top Candidate Skills
- Strategic Analytics & Decision Support: To translate complex data into actionable recommendations for product and business leaders.
- Communication
- Attention to details
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