Direct Client - Decision Scientist

About the Role

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.

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)

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: 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 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.

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

Candidate Requirements

Education

• Bachelor's degree in a relevant field preferred

How Success Is Measured

Customer Experience

• Order entry speed
• Quantum Metric digital experience data
• Error rate
• Customer adoption & engagement

Checkout & Transaction Performance

• Payment speed
• Cart completion rate
• Checkout success rate
• Transaction failure rate

Store Operations

• Order-to-window (OTW) time
• Window time
• Order accuracy
• Throughput
• Peak-hour performance

Product Health

• Feature adoption
• Feature utilization
• Customer satisfaction signals