About the Role
Ambitious and highly skilled Data Scientist Managers are needed to lead teams in developing cutting-edge machine learning solutions that improve customer experience.
Job Overview
We're looking for a talented Applied Scientist Manager to join our International Technology group (InTech), leading the Tools and Machine learning team (Tamale). As part of InTech, Tamale focuses on solving complex catalog quality problems using innovative machine learning and data analysis techniques.
Key Responsibilities
The successful applicant will work closely with business partners to identify opportunities for innovation, applying machine learning solutions to automate manual processes, scale existing systems, and improve catalog data quality. They will lead a team of scientists to design, develop, test, and deploy highly scalable distributed services, working closely with an engineering team to solve data quality issues at scale. This role requires influencing the scientific roadmap of the team, setting standards for scientific excellence, and working with state-of-the-art models, including image-to-text, Large Language Models, and Generative AI.
Requirements
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, or mathematics, or Master's degree and 4+ years of building machine learning models or developing algorithms for business applications
- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval, and Analytics
- Experience with leading a science team required
- Experience with building large-scale deep learning solutions for business required
- Experience programming in Java, C++, Python, or related languages required
About Amazon
Amazon is an equal opportunities employer, passionate about employing a diverse workforce. We make recruiting decisions based on your experience and skills, valuing your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a top priority.