- MS in a quantitative field plus 4 years of experience, or BS in a quantitative field plus 8 or more years of experience.
- Experience in designing analytic and/or algorithmic solutions to business or operational problems.
- Proficiency with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical software (e.g. R, SAS, Matlab).
- Excellent communication, writing and presentation skills.
- Ability to deliver under tight deadlines.
Amazon Private Brands is looking for a Data Scientist to join our Private Brands Discovery team in building Machine Learning solutions at scale. Private Brands applies Machine Learning, Statistics, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop statistical models and algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Economists, and Engineers, incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.
You 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 distributed services. You will invent and implement scalable ML and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.
As a Sr. Data Scientist, you bring business and industry context to science and technology decisions. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.
To learn more about Amazon Science, please visit https://www.amazon.science (https://www.amazon.science/).
- PhD in a quantitative field plus one or more years of experience.
- Experience with causal inference, deep learning, machine learning, and/or time series forecasting.
- Experience developing software in traditional programming languages (C++, Java, etc..).
- Experience working with Big Data technologies such as: AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza.
- Demonstrated ability to serve as a technical/scientific lead.
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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.