Amazon Applied Scientist III – AI Data Solutioning 

United States, Texas, Arlington 

928437815

We are seeking an innovative Applied Scientist III to drive our AI solutioning across our enterprise-wide transformation efforts. As a scientific leader, you will identify and devise new research solutions following a customer-obsessed approach to address complex business problems in organizational change and transformation. You'll leverage innovative AI and ML technologies including digital twin simulation and ambient intelligence capabilities to create novel solutions that accelerate and enhance our enterprise-wide transformation experiences. This includes developing real-time command center capabilities for monitoring change adoption, predictive models for transformation success, and AI-powered coaching systems that can scale transformation expertise across the organization.The ideal candidate combines deep expertise in at least one relevant computer science discipline(e.g., natural language processing, multimodal learning, reinforcement learning, or large-scale distributed systems), with a proven track record of delivering scientifically-complex AI solutions into production, particularly in the domains of predictive analytics, sentiment analysis, and digital twin simulations for organizational modeling. You'll work with massive, diverse datasets combining HR metrics, business performance data, employee sentiment, and market trends to build sophisticated ML models that can predict transformation needs and measure change effectiveness.You'll collaborate with cross-functional teams to translate ambiguous business requirements into innovative, scalable AI/ML solutions while contributing to the team's scientific agenda. You'll work closely with UX designers to ensure AI solutions are intuitive and human-centered, and partner with data engineers to build robust data pipelines and infrastructure that can support real-time transformation insights. We're looking for someone who displays comfort with ambiguity, demonstrates sophisticated scientific thinking, and brings a leadership style that balances innovation with pragmatism. Most importantly, you should be passionate about solving complex talent and organizational problems at scale through scientific invention and rigorous implementation, while maintaining a focus on delivering tangible business value.Key job responsibilities
Scientific Leadership and Innovation:
• Lead research initiatives in predictive modeling for organizational change readiness, developing novel approaches to forecast adoption patterns and resistance points
• Design and implement digital twin simulations for organizational structure optimization, incorporating multiple variables such as team dynamics, productivity metrics, and business outcomes
• Architect ambient intelligence systems that can detect and respond to workforce dynamics in real-time, providing contextual guidance and intervention recommendations
• Develop causal inference frameworks to measure transformation impact, isolating the effects of specific changes in complex organizational environments
• Drive the team's scientific agenda by proposing new methodologies for understanding and accelerating organizational change
• Drive innovation in natural language processing for contextual guidance and automated coaching featuresTechnical Implementation and Delivery:
• Lead the design, implementation, and successful delivery of solutions for scientifically-complex problems and systems in production, focusing on enterprise transformation tools and processes
• Build and deploy scalable ML solutions that combine multiple data modalities (HR metrics, sentiment data, business KPIs) to power real-time transformation insights
• Develop reusable components for automated workflow generation and personalized change guidance based on proven transformation patterns
• Create robust integration frameworks to connect solutions with existing PXT and enterprise tools/ data sources
• Lead the writing of internal document in alignment with business needsResearch and Analysis:
• Design and execute experiments to validate causal relationships in organizational change scenarios
• Develop novel methodologies for measuring transformation effectiveness using advanced statistical and ML techniques
• Create and validate prediction models for change readiness, adoption patterns, and transformation outcomes
• Lead research into new approaches for organizational modeling and simulationCross-functional Partnership:
• Partner with UX designers to translate complex AI capabilities into intuitive user experiences, ensuring transformation insights are accessible and actionable
• Work closely with data engineers to design and optimize data pipelines, storage solutions, and real-time processing systems
• Partner with product managers and business stakeholders to translate transformation challenges into technical requirements and solutions
• Partner cross functionally (with PXT and cross-org tech teams) to identify synergies and influence roadmaps across teams
• Guide technical decisions across teams to ensure coherent system architecture and optimal performance
• Influence decisions made by other teams to resolve bottlenecks in technologies that limit innovationDesign and Scale
• Design scalable solutions that can support both current known needs and future scaling
• Develop novel approaches for handling complex organizational data while maintaining privacy and security
• Create extensible frameworks for automated change management that can scale across diverse organizational contexts
• Create extensible frameworks for automated change management that can scale across diverse organizational contexts

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning