Applied Science Manager, Recommendations, Machine Learning, Personalization

Job summary
As the Applied Science Manager within Personalization, you will help build a team that leads creation and innovation on the next generation of Recommendation and Personalization technologies on Amazon. Our team owns creating recommendation solutions that understand long-term customer shopping patterns, Spanning Academia, research, and applied machine learning techniques operating at world-class scale, we focus on recommending the right product to the right customer at the right time. You will be surrounded by thought-leaders in the Personalization space who are patent-leaders within Amazon.

In Personalization we use state-of-the-art machine learning techniques and A/B testing to run experiments on some of Amazon’s most prominent and valuable pages. We work on a diverse range of products, building real-time, low-latency recommendation and ranking systems as well as building algorithms for understanding customer behavior and generating recommendations content. You will hone your skills in areas such as deep learning and collaborative filtering while building scalable industrial machine learning systems that handle millions of requests a day. You will lead a collaborative team of experienced engineers. You will have a unique opportunity to drive direct, measurable impact to our customers, powering features on Amazon.

About the team: Our team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones.

About you: You are an entrepreneurial Applied Science Manager with an interest in machine learning, data science, search, or recommendation systems. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products and hiring/coaching successful teams. You enjoy working hard, having fun, and making history!

Basic Qualifications

· A Master’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
· 4+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
· 1+ years of experience managing a software engineering or machine learning science team.
· Must have delivered features for at least one large-scale production system.

Preferred Qualifications

· PhD in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
· 6+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
· 2+ years of experience managing a software engineering or machine learning science team.
· Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
· A proven track record of hiring and developing software engineers or machine learning scientists.
· A strong sense of curiosity and willingness to learn quickly, building knowledge and skills that this role requires.
· A deep understanding of the software development lifecycle, and a track record of shipping software on time.
· Experience with the Scrum methodology (or similar alternatives) for agile software development.
· 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.
· Deep hands-on technical expertise in cloud-based distributed software design and development, especially utilizing AWS services.
· Knowledge of machine learning approaches and algorithms, and experience building complex highly-scalable systems that involve predictive models or applications of machine learning.
· Ability to handle multiple competing priorities in a fast-paced environment.


Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.