Applied Scientist, Private Brands - Discovery
The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists, Economists, and Engineers, that incubates and builds disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs state-of-the-art methods from deep learning, Bayesian optimization, multi-armed bandits, reinforcement learning, causal and statistical inference, econometrics, Natural Language Processing or any other novel approach that drives discovery of products across the customer journey. The solutions have to scale in production systems and the models can be trained in datasets of several terabytes. The team also works closely with academic researchers in ML and statistics at elite institutions called Amazon Scholars. These Scholars support us with science innovation, hypothesis formulation, and experimentation.
To be successful in this role, you need to be comfortable translating your science vision into specific plans for scientists and engineers, as well as partnering with product teams. This is a role that combines scientific excellence, organizational ability, product focus and business understanding. The ideal candidate will be an independent thinker who can make convincing, information-based arguments. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams.
Key job responsibilities
· Drive collaborative research and creative problem solving.
· Create experiments and prototype implementations of new learning algorithms and prediction techniques.
· Collaborate with engineering teams to implement software solutions for science problems.
· Innovate and contribute to Amazon’s science community and external research communities. Stay current on the state-of-the-art literature.
* Master's in Computer Science, Mathematics, Machine Learning, or related quantitative field
* Sound theoretical understanding of machine learning and statistical concepts, with deep and demonstrable expertise in at least one topic or application of machine learning.
* Hands-on experience (academic or industrial) building ML models
* Experience programming in Java, C++, Python, Scala, or a related language.
* Excellent communication, writing and presentation skills.
* Ability to deliver under tight deadlines.
* PhD degree in Machine Learning, Computer Science, Statistics, Operations Research, or related field; or equivalent.
* Experience with Deep Learning, NLP, or Reinforcement Learning
* Experience building and launching complex software systems
* Significant peer-reviewed scientific contributions in premier journals and conferences
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.