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Description

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 features

Technical 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 needs

Research 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 simulation

Cross-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 innovation

Design 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

About the team

The High Velocity Transformation team diagnoses, designs for, and delivers innovative change management and organization development solutions to drive positive transformations across the business. Our mission is to create human-centered transformation experiences that position Amazon employees to do the best work of their lives, while raising the bar on delivering for customers.

We are a team of transformation strategists, program leaders, systems and experience designers, and science and analytics experts ready to tackle a broad array of problems at the intersection of business and employee imperatives. We work collaboratively with other groups to drive business impact together.

Basic Qualifications

- 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

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

- Experience with large scale distributed systems such as Hadoop, Spark etc.

- - Experience with autonomous agents, large multimodal models (especially vision-language models), reinforcement learning (RL), sequential decision making, and digital Twin Technology

- - Experience architecting multi-modal data integration systems that combine HR, business metrics, and external market data

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.