Applied Scientist- Finance Transformation/Forecasting, Corp FP&A Technology

Amazon•Seattle, WA

14d

About The Position

Within Amazon’s Corporate Financial Planning & Analysis team (FP&A), we enjoy a unique vantage point into everything happening within Amazon. This is exciting opportunity for scientist to join our Financial Transformation team, where you will get to harness the power of statistical and machine learning models to revolutionize finance forecasting that spans entire company and business units. As a key player in this innovative group, you'll be at the forefront of applying state-of-the-art scientific approaches and emerging technologies to solve complex financial challenges. Your deep domain expertise will be instrumental in identifying and addressing customer needs, often venturing into uncharted territories where textbook solutions don't exist. You'll have the chance to author Finance AI articles, showcasing your novel work to both internal and external audiences. Key job responsibilities Your role will involve developing production-ready science models/components that directly impact large-scale systems and services, making critical decisions on implementation complexity and technology adoption. You'll be a driving force in MLOps, optimizing compute and inference usage and enhancing system performance. Beyond technical prowess, you'll contribute to financial strategic planning, mentor team members, and represent our tech. organization in the broader scientific community. This role offers a perfect blend of hands-on development, strategic thinking, and thought leadership in the exciting intersection of finance and advanced analytics. Ready to shape the future of financial forecasting? Join us and let's transform the industry together!

Requirements

3+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice To Haves

Experience using Unix/Linux
Experience in professional software development

Responsibilities

developing production-ready science models/components that directly impact large-scale systems and services
making critical decisions on implementation complexity and technology adoption
driving force in MLOps, optimizing compute and inference usage and enhancing system performance
contribute to financial strategic planning
mentor team members
represent our tech. organization in the broader scientific community