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Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success. WISE (Workforce Intelligence powered by Scientific Engineering) delivers the scientific and engineering foundation that powers Amazon's enterprise-wide workforce planning ecosystem. Addressing the critical need for precise workforce planning, WISE enables a closed-loop mechanism essential for ensuring Amazon has the right workforce composition, organizational structure, and geographical footprint to support long-term business needs with a sustainable cost structure.

We are looking for a Sr. Applied Scientist to join our ML/AI team to work on Advanced Optimization and LLM solutions. You will partner with Software Engineers, Machine Learning Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space.

Key job responsibilities

• Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams
• Priority management - manage diverse requests and dependencies from teams
• Process improvements – define, implement and continuously improve delivery and operational efficiency
• Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations
• Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations

To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better. - 3+ years of building machine learning models for business application experience