Sr. Applied Scientist
- Dublin, Ireland
Selling Partner Services (SPS) is the custodian of the selling partners' journey through Amazon.com and is responsible for several key elements of Amazon's business. The primary goals of SPS are to drive awareness and motivation to sell among the global entrepreneurs, simplify onboarding and provide education throughout the Selling Partner lifecycle, ensure price competitiveness, and finally, drive product discovery so partners can effectively convey their brand/product story.
The T1 Seller Development (T1SD) organization owns the charter to drive WW seller growth on Amazon. Our products are strategically important to the long term growth of Amazon's consumer businesses, and our organization's initiatives are highly visible to Amazon's executive leadership. We will accomplish the ambitious growth goal through building innovative and scalable technical products and platform.
We are looking for a customer obsessed Applied Scientist who can apply the latest research, state of the art algorithms and machine learning to build highly scalable systems in the e-commerce domain. Does the challenge of advancing one of the world's most scalable, reliable, and secure e-commerce platforms that drives billions of dollars in revenue excite you? Have you ever wanted to work on machine learning problems that will make a lasting impact, solving key problems that impact the experience of millions of Amazon customers? If you are passionate about solving complex problems, in a challenging environment, we would love to talk with you.
As a member of our team you will develop and evaluate machine learning models using large data-sets and cloud services to drive seller growth. Working closely with best-in-class engineers you will have the opportunity to apply a variety of machine learning algorithms, including deep learning, and work on one of the world's largest data sets to influence the long term evolution of our technology roadmap. You will need to be entrepreneurial, able to deal with ambiguity and work in a highly collaborative environment.
To know more about Amazon science, Please visit https://www.amazon.science
• Ph.D./M.S. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
• 6+ years of hands-on experience in predictive modeling, analysis, and Machine learning
• 3+ years hands-on experience in Python, Scala, Java, C#, C++ or other similar languages
• Proficiency in model development, model validation and model implementation for large-scale applications
• Ability to convey mathematical results to non-science stakeholders
• Strength in clarifying and formalizing complex problems
• Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field;
• 6+ years of practical experience applying ML to solve complex problems in an applied environment;
• Significant peer-reviewed scientific contributions in premier journals and conferences;
• Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis;
• Experience with defining research and development practices in an applied environment;
• Experience working with Deep Learning frameworks (MxNet, TensorFlow, etc.);
• Proven track record in technically leading and mentoring scientists;
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
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
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