Amazon
Sr. Applied Scientist, Private Brands Intelligence - Sourcing Guidance
Amazon, Seattle, Washington, us, 98127
Job ID: 2727659 | Amazon.com Services LLCThe Private Brands team is looking for an Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights. We are an interdisciplinary team of Scientists, Engineers, and Economists and primary focus on building optimization and machine learning solutions in supply chain domain with specific focus on Amazon private brand products.
Key job responsibilitiesYou will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models.
This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a senior scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.
We are particularly interested in candidates with academic and/or practical background in Operations Research and Machine Learning. Experience in applying Operations Research and/or ML to supply chain problems is a plus.BASIC QUALIFICATIONS
- 5+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Experience with conducting research in a corporate settingPREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems such as Hadoop, Spark etc.
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Key job responsibilitiesYou will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models.
This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a senior scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.
We are particularly interested in candidates with academic and/or practical background in Operations Research and Machine Learning. Experience in applying Operations Research and/or ML to supply chain problems is a plus.BASIC QUALIFICATIONS
- 5+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Experience with conducting research in a corporate settingPREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems such as Hadoop, Spark etc.
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