DESCRIPTION

The 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 responsibilities
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 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 setting

PREFERRED 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.

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

USA, WA, Seattle