המקום בו המומחים והחברות הטובות ביותר נפגשים
As an Applied Scientist, you will have the opportunity to play a key role in owning and driving the design and development of search and recommendation experiences for our customers. You will be working in a fast-paced, cross-disciplinary team of engineers and business stakeholders who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. You will also get the freedom and encouragement to explore your own ideas and the reward of seeing your contributions benefit Amazon and its employees worldwide.
Key job responsibilities
• Analyse and extract relevant information from large amounts of purchasing data to help automate and optimize key processes.
• Research, develop and implement novel machine learning and statistical approaches for improving the user experience in the procurement domain.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
Bangalore, KA, IND
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
- Have publications at top-tier peer-reviewed conferences or journals
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