Job Description
DESCRIPTION
Join our Private Brand Intelligence (PBI) organization in building Data Science driven solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.
PBI applies Generative AI, Machine Learning, Statistics, and Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop ML/Econ models and algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers 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 and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed solutions. 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 science problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. If you are interested in Machine Learning, Generative AI, and large-scale intelligent solutions then this is the role you have been looking for.
We are a Day 1 team, with a charter to be disruptive through the use of Data Science and Machine Learning. You will start on green field projects working with engineers to bring our models to life as well as data products that other teams can benefit from. We are an inclusive team, and are looking for Data Scientists that aren't averse to learning and building and or optimizing ML models alongside our engineers, product managers and business partners.
As a Data Scientist on the team, you will drive improvements to our business, collaborating with scientists, economists, engineers and highly-engaged stakeholders to deliver actionable insights continuously. We’re truly an agile shop: we work closely with users, deliver features with high frequency, can pivot on a dime when needed, and are passionate about solving customer pain points. We are looking for data science leaders who share our vision for continuously improving the customer experience, who are motivated by challenging business problems and who love thinking big.
Key job responsibilities
* You will take the lead on large projects that span multiple teams. The problems you solve will be ambiguous, requiring both technical and domain expertise. You will deliver significant benefits to business with minimal assistance.
* You need to understand challenges in your teams’ business area, the applicability of relevant data science disciplines, and interactions among systems. You will influence your team’s technical and business strategy by making insightful contributions to team priorities and approach.
* You will make solutions simpler. You will optimize connected systems using their dynamics. You will improve the consistency and integration between your team’s solutions and the work being done by related teams.
* You will improve the work done by others, either via a collaborative effort or by increasing their scientific knowledge, using specialized tools or advanced techniques. You will lead and actively participate in scientific reviews for your team and others.
* You are able to communicate your ideas effectively to achieve the right outcome for your team and customer including when to make appropriate trade-offs. You harmonize discordant views and lead the resolution of contentious issues.
* You actively participate in the hiring process and improve the skills and knowledge of others via mentoring.
BASIC QUALIFICATIONS
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 4+ years of data scientist experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
- Experience documenting modeling for technical and business leaders
- Experience working with scientists, economists, software developers, or product managers
- 3+ years of hands-on industrial experience with two or more of the popular statistical modeling and machine learning techniques such as regression, classification, clustering, deep learning, etc.
Job Tags
Full time,