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Decision Scientist

Spectraforce Technologies
United States, Washington, Seattle
Aug 02, 2026
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

Applied = 0

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