Sr. Applied Scientist, Private Brands Intelligence - Sourcing Guidance

Job ID: 2727659 | Amazon.com Services LLC

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 with a primary focus on building optimization and machine learning solutions in the supply chain domain, specifically for 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 will bring business and industry context to science and technology decisions, set the standard for scientific excellence, and make decisions that affect the way we build and integrate algorithms. Your solutions will be exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You will tackle intrinsically hard problems, acquiring expertise as needed, and decompose complex problems into straightforward solutions.

BASIC QUALIFICATIONS

1. 5+ years of building machine learning models for business application experience
2. PhD, or Master's degree and 6+ years of applied research experience
3. Experience programming in Java, C++, Python or related language
4. Experience with neural deep learning methods and machine learning
5. Experience with conducting research in a corporate setting

PREFERRED QUALIFICATIONS

1. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
2. 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

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