Senior Applied Scientist
- Nashville, TN
Not many teams aspire to zero. Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com.
WW R&R is an agile, innovative organization dedicated to 'making zero happen' to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing groundbreaking products and driving operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future - we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon - returns, recommerce, and rentals.
Amazon WW R&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop innovative product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus.
In this role, you would
- Use machine learning and analytical techniques to create scalable solutions for business problems.
- Analyze and extract relevant information from large amounts of historical business data to help automate and optimize key processes.
- Design, development and evaluation of highly innovative models for predictive learning.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Research and implement novel machine learning and statistical approaches.
- Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.
- Technically lead and mentor other scientists in team.
We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth.
Amazon is earth's most customer-centric company and through WW R&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
- PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
- 6+ years of hands-on experience in predictive modeling, analysis and applying ML to solve complex problems.
- Algorithm and model development experience for large-scale applications.
- Skills with Java, C++, or other programming language, as well as with SQL, R, MATLAB, Python or similar scripting language.
- Strong communication and data presentation skills. Ability to distill customer requirements into problem definitions, and dealing with ambiguity.
- Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, NLP, recommendation systems, dialogue systems, information retrieval;
- Significant peer reviewed scientific contributions in premier journals and conferences;
- Strong personal interest in learning, researching, and creating new technologies with high customer impact;
- Experience with defining research and development practices in an applied environment;
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
- Ability to work on a diverse team or with a diverse range of coworkers.
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
We believe passionately that employing a diverse workforce is central to our success and we make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, gender, disability, sexual orientation, race, religion or belief.
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