Decision Scientist

• Influence product strategy, roadmap priorities, and investment decisions
• Work with large-scale data across cloud and on-premises environments
• Build AI-enabled analytics tools and self-service reporting capabilities
• Lead experimentation, forecasting, and product measurement initiatives
• Collaborate with cross-functional product, engineering, UX, and operations teams

• Analyze product, operational, transaction, and digital experience performance to identify trends, risks, root causes, and opportunities.
• Develop recommendations that influence product prioritization, roadmap planning, feature optimization, and investment decisions.
• Build analytical models, forecasts, scenario-planning tools, and opportunity-sizing assessments.
• Define key performance indicators and monitor product, operational, and business outcomes.
• Quantify business impact and measure return on investment for product initiatives.

• Define measurement strategies and success criteria for new products, features, and digital experiences.
• Design and evaluate A/B tests, pilots, and experiments.
• Measure adoption, engagement, conversion, transaction success, operational efficiency, and feature utilization.
• Create standardized product measurement frameworks across platforms and channels.
• Evaluate pilot results and provide recommendations for broader implementation.

• Build and maintain product health scorecards, performance dashboards, and automated reporting solutions.
• Develop AI-enabled and self-service analytics tools for product teams.
• Automate recurring analysis, monitoring, and reporting activities.
• Partner with data engineering and analytics teams to improve data quality, accessibility, and reporting capabilities.
• Enhance existing dashboards and data products based on evolving business needs.

• Lead analysis of complex and ambiguous business questions.
• Develop hypotheses, research approaches, measurement plans, and actionable recommendations.
• Translate technical analysis into clear business implications.
• Create executive-ready presentations covering performance, risks, opportunities, and recommended actions.
• Present findings to product leadership and senior executives.
• Promote best practices in decision science, experimentation, product analytics, and AI-enabled reporting.

• Bachelor’s degree in analytics, data science, statistics, economics, business, computer science, or a related field preferred.
• At least four years of experience in strategic analytics, product analytics, or decision support.
• At least five years of experience communicating analytical findings and producing detail-oriented deliverables.
• Advanced proficiency in SQL, Excel, Python, R, SAS, Tableau, or Power BI.
• Experience with Azure Data Lake Storage, Azure SQL Server, Oracle, AWS, on-premises systems, and web-based data sources.
• Experience performing exploratory data analysis, data cleansing, transformation, aggregation, and large-scale data manipulation.
• Knowledge of experimental design, A/B testing, forecasting, and scenario planning.
• Ability to explain complex technical findings to non-technical audiences.
• Strong business acumen and understanding of operational and digital product processes.

• Azure
• Oracle
• SQL Server
• Python, R, and SAS
• Tableau or Power BI
• Microsoft Office Suite
• Smartsheet