Description AMZL Strategic Planning is seeking an experienced Data Science leader, to lead the development of algorithmic tools, supporting Strategic Planning. You are an outstanding Data Scientist with background in Operations Research. Have passion for technology, complex data sets but tool/tech agnostic. You determine what technology works best, for the problem at hand and innovate accordingly. You can explain complex concepts to your non-technical customers in simple terms. You are a leader who is uncompromisingly detail oriented, smart, efficient and driven to help our business succeed. You develop sophisticated algorithms that involve learning from large amounts of data, designing solutions to resolve long-term Logistics Network Topology design constraints, capacity constraints and improve demand distributions for the complex Last Mile Logistics network. Key job responsibilities In this role, you will work with other Research Scientists, Data Scientists, BIEs and DEs and with Business Leaders. You develop your own scientific approaches and partner with teams as they deploy algorithmic solutions to our stakeholders. You will partner with business leaders in evaluating long-term strategic AMZL network choices, speed initiatives, topology build plan optimization. You present strategy papers to our senior-most leaders to drive long-term impact. To accomplish this, we expect you to have a strong research background in at least one of the following disciplines: Operations Research, Operations Management, Statistics, or applied mathematics. You should also have strong business domain knowledge in transportation, distribution operations, logistics management with some knowledge of inventory management theory and practice. You should have a publication record demonstrating technical depth, as well as, consideration of practical aspects in your work. Experience partnering with companies on high-stakes R&D or consulting is a plus. A day in the life - Design, develop complex mathematical, simulation and optimization models ; apply them to define strategic optimization needs - Drive the appropriate business and technical solutions in the areas of 'Topology Design' optimization - Apply theories of mathematical optimization, including linear programming, integer programming, dynamic programming, network flows and algorithms to design optimal solutions - Prototype these models by using modeling languages such as R, Scala, Python. Be conversant with foundational elements of Generative AI, AWS stack - Influence solution roadmap, onboard new technologies onto Science team's toolbox, mentor other Scientists and lead from a scientific perspective About the team AMZL Strategic Planning Analytics is focused, enabling Long-Term (3 –7 years) Planning capabilities for managing a cost effective logistics and distribution network. There are various strategic questions team is attempting to solve, such as: optimal Topology Design, given the location/site availability constraints. Can we predict accurately, the fulfillment pattern for different customer clusters at new locations? What techniques can evaluate new site/facility recommendation for long term growth? We predict network utilization improvements over the horizon, with simulation of how our choices will perform. Our analysis efforts recommend, multi-year strategic goals to reduce cost, increase speed and quality. Basic Qualifications - 4+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment Preferred Qualifications - Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent) - Experience in a ML or data scientist role with a large technology company 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 $125,500/year in our lowest geographic market up to $212,800/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.