Sr. Research Scientist, Planning
SCOT Planning organization focuses on research areas and tools that help automate and optimize the week 0 to 5 year planning across all WW regions including IB planning and automation, Inventory Prediction and Entitlement and FC Capacity Planning and topology.
Over the years, Amazon's planning systems landscape has grown increasingly complex and the recent shifts in the fulfillment strategy with the advent of regionalization and multi-tier network design will continue to amplify this complexity. Historical investments in the systems and processes specifically around inventory units, dollars, and cube planning have been managed under different teams within SCOT and continue to present opportunities to better connect the dots to deliver better business results for our customers. To drive synergies and to move towards the vision to manage inventory and capacity at the right level of granularity, a new planning organization has been formed to establish a single source of truth for critical planning functions. The Senior RS role will be responsible for the developing science based solutions that span across the planning horizon and optimize for customer-focused outcomes. If you are interested in diving into a multi-discipline, high impact space this team is for you. So far, we utilized models from various science disciplines such as: Mixed Integer , Random Forest (or other ML techniques), /probabilistic model, economic analysis, to name a few.
In addition to network, we also use and techniques to evaluate new facilities recommendation for long term estimates, We use to approximate the network, and simulation of how our choices will perform. The team is a mixture of Software Engineers, Operations Research Scientists, Applied Scientists, Business Intelligence Engineers and Product Managers.
We are looking for a Sr. Research Scientist who has a knowledge of analyzing fulfillment data using and . Those who are strong in space should have a breadth of other ML experience in a production environment using techniques. This role will focus on expanding our reach to analyze various fulfillment and for Amazon's network worldwide.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age
We are open to hiring candidates to work out of one of the following locations:
New York, NY, USA
- 3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience
- PhD, or Master's degree and 5+ years of quantitative field research experience
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
- Experience communicating qualitative research methods and findings to non-qualitative researchers
- Experience converting research studies into tangible real-world changes
- Experience with discrete and continuous optimization methodologies and algorithms
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/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. Applicants should apply via our internal or external career site.