Applied Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services

## Responsibilities - Design and implement machine learning models that power recommendation systems for job seekers and recruiters, ensuring high performance, scalability, and reliability at global scale. - Collaborate with engineers, scientists, and product managers to define requirements, create solutions, and deliver products that improve the hiring experience. - Participate in the full software development lifecycle including scoping, design, coding, testing, documentation, deployment, and maintenance of recommendation systems and ML models. - Solve complex ML problems using optimal data structures and algorithms, making thoughtful trade-offs between efficiency and maintainability. - Stay current with scientific literature and develop novel approaches that address business challenges in talent acquisition. You will have the opportunity to provide feedback on scientific work across the organization helping the entire Intelligent Talent Acquisition organization improve. ## Requirements - Experience in solving business problems through machine learning, data mining and statistical algorithms - Experience programming in Java, C++, Python or related language - Speak, write, and read fluently in English - Experience that includes strong analytical skills, attention to detail, and effective communication abilities ## Nice to Have - PhD in computer science, machine learning, engineering, or related fields - Experience in designing experiments and statistical analysis of results - Experience in patents or publications at top-tier peer-reviewed conferences or journals ## Benefits - Opportunity to solve complex problems with significant impact by creating systems that make Amazon’s entire hiring ecosystem more effective - Collaborating with scientists across the organization - Working in a collaborative environment with regular knowledge sharing and mentorship opportunities - Impacting Amazon’s ability to find and hire exceptional talent globally