Want to help invent next generation technologies in optimization and recommender systems? Would you like a unique opportunity to directly impact millions of customers every day, and drive billions of dollars of impact? We’ve got the perfect job for you.
Amazon’s ISS Science team is looking for a seasoned Applied Science Manager to help build a production scaled personalized recommendation service that identifies growth levers at every step of a seller’s journey at Amazon and ultimately leads to seller prosperity on Amazon. Owning one of the largest scale machine learning projects in the company, you will lead the team that builds automated systems to optimize success levers for sellers on Amazon’s selling partner portal. You will help push the boundaries of applied science in areas such as deep reinforcement learning, multi-armed bandits, natural language understanding, and counterfactual learning while building scalable industrial systems that can process billions of requests per day.
We are looking for an entrepreneurial manager with strong leadership, great business and technical judgment, clear communication skills, and strong track record of delivery.
As a part of this role, you will:
- Define the long-term development, science and business strategies for the team
- Build and manage a team of industry-leading applied scientists
- Foster career growth and a strong team culture
- Recruit, hire, mentor, and coach technical staff
- Interface with internal customers to understand requirements, set priorities and communicate direction and progress
- Own all operational metrics and support for your team’s software
- Manage the agile development process and methodology to deliver value to customers
This is a rare opportunity to lead a highly leveraged team that drives a massive impact at Amazon. We are defining the future of content optimization at the biggest internet retailer on Earth. We hope you will join us!
- MS or PhD in Machine Learning, Computer Science, Statistics, Applied Math or related field
- 3+ years of managing applied science teams
- Demonstrated use of modeling and optimization techniques tailored to meet business needs
- Highly motivated self-starter with bias for innovative thinking
- Excellent written and oral communication skills
- Excellent business judgement
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- Experience building highly scalable, complex real-time recommender/optimization systems.
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Experience communicating with users, other technical teams, and senior management to collect requirements, describe software product features, technical designs, and product strategy.
- Experience influencing software engineers’ best practices within your team.