Interested in using the latest, cutting edge machine learning and science to improve the Amazon employee experience? This role provides applied science leadership to the organization that develops and delivers data-driven insights, personalization, and nudges into Amazon's suite of talent management products to help managers, employees, and organizational leaders make better decisions and have better, more equitable outcomes.Key job responsibilitiesAs the Principal Applied Scientist for GTMC SIERRA, you will be responsible for providing scientific thought leadership over multiple applied science and engineering teams. Each of these teams has rapidly evolving and complex demands to define, develop, and deliver scalable products that make work easier, more efficient, and more rewarding for Amazonians. These are some of Amazon's most strategic technical investments in the people space and support Amazon's efforts to be Earth's Best Employer. In this role you will have a significant impact on 1.5 million Amazonians and the communities Amazon serves.You will also play a critical role in the organization's business planning, work closely with senior executives to develop goals and resource requirements, influence our long-term technical and business strategy, and help hire and develop engineering and science talent. You will provide science thought leadership and support to business partners, helping them use the best scientific methods and science-driven tools to solve current and upcoming challenges and deliver efficiency gains in a changing market.About the teamGlobal Talent Management & Compensation (GTMC) SIERRA (Science, Insights, Experience, Research, Reporting & Analytics) is a horizontal, multi-disciplinary organization whose mission is to be a force multiplier for the broader GTMC organization and our key customer cohorts. We accomplish this by using our expertise in data analytics and science, economics, machine learning (ML), UX, I/O psychology, and engineering to build insights and experiences that raise the bar in understanding and shaping decision making at scale by integrating within and across talent journeys as well as through self-service tools and closed loop mechanisms outside of those journeys. Our portfolio of products spans foundational data sources, metrics, and research through to finished features and products that our end-customers interact with on a daily basis.We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USAAdvanced degree (e.g., M.S. or PhD) in computer science, statistics, engineering, mathematics or related discipline.10+ years of experience building and applying ML models to solve complex problems for large-scale applications and staying current with the latest science e.g. deep Learning models and Generative AI.Experience with leadership of experienced scientists as well as a record of developing junior scientists for a career track in a business environment.Familiar with one or more programming languages such as C/C++, Java, Perl or Python.Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our customer's organisation.Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.Experience implementing algorithms, tailored to business needs and tested on large data sets.Strong research track record.Experience with a broad range of ML systems such as personalized recommendations, forecasting and developing generative AI solutions.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pa