Direct Client - Decision Scientist

The AES Group; Washington (District of Columbia); Hybrid; USD 120,000 - 180,000; Full time

Job summary

The AES Group in Seattle, WA is seeking a Decision Scientist to partner with product managers, engineering, UX, and operations. You will drive data-informed decisions across product ordering experiences using advanced analytics, experimentation, and AI-enabled insights.

The ideal candidate translates complex data into actionable recommendations for product and business leaders and helps improve customer experience and operational efficiency.

Qualifications

• Translate complex business problems into practical data solutions.
• Create and implement data-driven workflows.
• Work with data dictionaries and data definitions.
• Work with data engines / platforms and structure data.
• Gather and translate business requirements into data solutions.
• Collaborate across business and tech teams to develop solutions.
• Connect business objectives with data and analytics.
• Design data transformations and analytical workflows.

Responsibilities

• Analyze product, operational, and customer experience performance to identify trends and opportunities.
• Build models, forecasts, and scenario planning tools to inform prioritization and ROI.
• Define measurement strategies for new products and evaluate A/B tests.
• Build scalable dashboards and AI-enabled analytics to empower product managers.
• Lead cross-functional teams through complex business questions and synthesize results into recommendations.
• Develop executive-ready narratives to communicate performance and actions.
• Promote best practices in product measurement and decision science.

Skills

Azure data lake

SQL Server

Oracle

Excel

SQL

SAS

R

Python

Tableau/Power BI

A/B testing

Education

Bachelor's degree

Tools

Databricks

Job description

Role: Direct Client - Decision ScientistLocation: Seattle WA - Hybrid.

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
• Microsoft Office SuiteSmartsheetNice to HaveDatabricks 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 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.

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.